- Research
- Open access
- Published:
Vertical distribution patterns and drivers of soil bacterial communities across the continuous permafrost region of northeastern China
Ecological Processes volume 11, Article number: 6 (2022)
Abstract
Background
Soil microorganisms in the thawing permafrost play key roles in the maintenance of ecosystem function and regulation of biogeochemical cycles. However, our knowledge of patterns and drivers of permafrost microbial communities is limited in northeastern China. Therefore, we investigated the community structure of soil bacteria in the active, transition and permafrost layers based on 90 soil samples collected from 10 sites across the continuous permafrost region using high-throughput Illumina sequencing.
Results
Proteobacteria (31.59%), Acidobacteria (18.63%), Bacteroidetes (9.74%), Chloroflexi (7.01%) and Actinobacteria (6.92%) were the predominant phyla of the bacterial community in all soil layers; however, the relative abundances of the dominant bacterial taxa varied with soil depth. The bacterial community alpha-diversity based on the Shannon index and the phylogenetic diversity index both decreased significantly with depth across the transition from active layer to permafrost layer. Nonmetric multidimensional scaling analysis and permutation multivariate analysis of variance revealed that microbial community structures were significantly different among layers. Redundancy analysis and Spearman’s correlation analysis showed that soil properties differed between layers such as soil nutrient content, temperature and moisture mainly drove the differentiation of bacterial communities.
Conclusions
Our results revealed significant differences in bacterial composition and diversity among soil layers. Our findings suggest that the heterogeneous environmental conditions between the three soil horizons had strong influences on microbial niche differentiation and further explained the variability of soil bacterial community structures. This effort to profile the vertical distribution of bacterial communities may enable better evaluations of changes in microbial dynamics in response to permafrost thaw, which would be beneficial to ecological conservation of permafrost ecosystems.
Introduction
Permafrost is soil that remains continuously frozen for at least two years and underlies about 25% of terrestrial area in the Northern Hemisphere (Doherty et al. 2020). It is estimated that permafrost soil contains approximately 1300 Pg of carbon which is equal to half of the global soil organic carbon (Schuur et al. 2015; Zhou et al. 2020). During the past few decades, global warming has caused widespread permafrost thawing, which has induced a significant reduction of soil organic matter and the subsequent release of greenhouse gases (primarily carbon dioxide (CO2) and methane (CH4)) because of increased microbial activity, and potentially generate positive feedback to climate warming (Mackelprang et al. 2011; Graham et al. 2012; Heslop et al. 2019). Permafrost thaw has also led to the deepening of the active layer, which is the surface of permafrost that undergoes frequent environmental disturbances via seasonal freezing and thawing (Kim et al. 2016). Studies have reported that microbial biomass and metabolic activity were higher in the active layer of soil and decreased towards deeper soil layers (Frankfahle et al. 2014; Koyama et al. 2014). Even though deeper permafrost layer is considered to be an extreme environment with low temperature and nutrient availability, it is a relatively stable habitat for microbial communities (Jansson and Taş 2014). Transition layer refers to soil above the permafrost interface and is the boundary connecting the active layer and permafrost layer (Deng et al. 2015; Aksenov et al. 2021). Differences in physicochemical and biological properties imply that the factors shaping microbial communities may be different among soil layers and the composition and diversity of microbial communities in different layers changes in response to thawing (Mackelprang et al. 2011; Deng et al. 2015). Therefore, a better understanding of the changes in microbial communities in different soil layers and the factors that shape these communities is important to predict the potential microbial processes and permafrost ecosystem functions in a changing climate.
Soil depth profiles provide heterogeneous environmental conditions for microorganisms and therefore serve as a good model for predicting the variations in thawing permafrost. Investigations of the Tibetan Plateau and the Arctic have shown that microbial communities varied with soil depth, and that the abundance and diversity of soil microbial taxa declined with depth with the transition from the surface active layer to the underlying permafrost layer (Steven et al. 2008; Mackelprang et al. 2011; Frankfahle et al. 2014; Koyama et al. 2014; Taş et al. 2014; Wei et al. 2014; Deng et al. 2015; Hu et al. 2015, 2016; Frey et al. 2016). These studies revealed that the vertical distribution patterns of microbial communities were affected by corresponding soil properties such as soil nutrient availability and moisture content. Furthermore, recent studies have found that bacterial and fungal communities occurring in the active layer and permafrost respond differently to permafrost thaws at different depths (Wu et al. 2018; Sannino et al. 2021). However, most of these available studies of permafrost microbial communities included only one or a limited number of soil cores from each location. Studies focusing on shifts in microbial communities along soil depth profiles across multiple sampling sites over broad geographic scales are less affected by the heterogeneity of the soil ecosystems themselves and are statistically more confident (Deng et al. 2015; Chen et al. 2017). Hence, such studies are still needed to assess the spatial variability and dynamics of permafrost ecosystems in light of anticipated climate change.
Distributed in the southeast margin of the Eurasian cryolithozone, the latitudinal permafrost in northeastern China is sensitive to climate change and has experienced degradation owing to recent climate warming (Jin et al. 2007). Permafrost thaw in this region has resulted in substantial increases in the mean annual ground temperature and the depth of the active layer (Wei et al. 2011). Nevertheless, except for studies on the Sanjiang Plain (Zhou et al. 2017), in Mo-he (Dan et al. 2014), and along the China-Russia Crude Oil Pipeline (Yang et al. 2012), the microorganisms and distribution patterns of microbial communities in this unique permafrost soil remain relatively unexplored (Ren et al. 2018).
Therefore, in this study, we analyzed the vertical distribution patterns and drivers of bacterial communities in different soil layers in the continuous permafrost region of northeastern China. A total of 90 samples collected from 10 sites across the whole region were used to characterize the microbial communities by high-throughput Illumina sequencing. In agreement with previous studies, we hypothesized a decrease in both the number and genetic diversity of bacteria with the increase in soil depth. We further hypothesized that soil chemical-physical properties would have substantial influences on the diversity and composition of the bacterial communities due to stratified soil abiotic conditions of different soil layers. To test these hypotheses, we aimed to determine: (1) the differences in the composition and diversity of bacterial community along the vertical depth, and (2) the main factors driving the distribution of the bacterial community in the permafrost soil.
Materials and methods
Soil sampling and analysis
The soils at 10 sites in the continuous permafrost region of northeastern China were sampled during August 2015 (Fig. 1). The active layer thickness of the study sites we chosen were measured using a steel probe to reach the freezing solid and were all approximately 50 cm. At each site, three randomly selected 2 m × 2 m plots within an area of 20 m × 20 m were selected as replicates. In each plot, five 70 cm soil cores were collected, and soil samples were collected from three depth intervals representing the active layer (0–20 cm, refers to the surface thawed soil at the time of sampling within the organic horizon), the transition layer (20–50 cm, contains soil within the seasonally thawed mineral horizon, that is above the permafrost interface) and the permafrost layer (50–70 cm, refers to soil at or below the permafrost interface). The five subsamples from each depth within the same plot were pooled into a single soil sample, resulting in 90 soil samples (10 sites × 3 plots × 3 layers). Soil moisture, temperature and salinity were synchronously measured using an in-situ soil testing device (TZS-PHW-4, China). The soil samples were immediately transported to the laboratory while stored on ice. After being sieved through a 2 mm standard mesh, the soils were divided into two portions. One portion was stored at 4 °C for analysis of soil properties, and the other was stored at − 80 °C for microbial analyses (All permafrost layer soil were stored at − 80 °C).
Soil texture was measured using a particle size analyzer (Malvern Instruments, Malvern, UK) and classified by the universal criteria of soil particle size (clay < 0.002 mm, silt 0.02–0.002 mm, sand > 0.02 mm). Soil pH was determined by suspending soil in a 1:2.5 (w/v) aqueous solution and then analyzed by a pH electrode (Kalra 1995). Soil total nitrogen content (TN) and total carbon content (TC) were measured with an element analyzer (EL Ш, Elementar, Germany). The mass ratio of soil carbon:nitrogen (C/N) was calculated based on the TC and TN. The Mo-Sb anti-spectrophotometry method was used to measure soil total phosphorus content (TP) after digestion of the samples with concentrated HClO4–H2SO4. Soil total organic carbon (TOC) was determined by the K2Cr2O7 oxidation method as described in Walkley (1947). Soil available phosphorus (AP) was extracted with 0.5 M NaHCO3 and measured using a colorimetric method. Soil available N (AN) was measured using a continuous flow analyzer (SAN++ , Skakar, Breda, Holland) after extraction with 2 M KCl (soil to water ratio of 1:5).
DNA extraction, amplification and sequencing
Genomic DNA of each soil sample was isolated using the PowerSoil DNA Isolation Kit (MO BIO, USA) according to the manufacturer's instructions. The extracted DNA was qualitatively evaluated by agarose gel electrophoresis and the concentration was determined using a Nanodrop 2000 (Thermo, USA). To amplify the V4 hypervariable region of the 16S rRNA gene, we used the 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 909R (5′-CCCCGYCAATTCMTTTRA GT-3′) primers with unique barcodes. The PCR amplification process was performed as previously described (Gibson et al. 2014), after which the products were purified using an AxyPrepDNA Gel Extraction Kit (AXYGEN, California, USA). The resultant PCR products were then combined at equimolar concentrations before being sequenced using the Illumina Miseq platform at the Chengdu Institute of Biology, Chinese Academy of Sciences.
Processing of sequencing data
The obtained raw sequence data were analyzed using the Quantitative Insights into Microbial Ecology (QIIME) pipeline (QIIME v.1.8.0; http://www.qiime.org). Paired-end reads with at least a 50-bp overlap and < 5% mismatches were combined using FLASH (version 1.0.0). A threshold of average quality scores > 30 over 5-bp window size was used to trim the unqualified sequences using BTRIM (version 1.0.0; Kong 2011). Any joined sequences with ambiguous bases and lengths < 200 bp were discarded. After trimming of ambiguous bases, joined sequences with lengths between 240 and 260 bp were subjected to chimera removal by U-Chime (Edgar et al. 2011). The resultant high-quality sequences were clustered into operational taxonomic units (OTUs) at the level of 97% similarity using UCLUST (Edgar 2010). Sequences were subsequently aligned using the PyNAST software, after which OTUs were classified against the 13_8 Greengenes database and taxonomic assignments were based on their respective taxonomy files (Werner et al. 2012). A taxon filtering script provided by QIIME was applied to separate the OTU tables of individual microbial taxa, which were then used to analyze the abundance of specific taxa. The community compositions were then described by the relative abundance of sequences that were assigned to each taxon. To compute the alpha diversity, we calculated the Shannon diversity index and the phylogenetic diversity index (Faith 1992). Beta-diversity metrics were introduced by the unweighted UniFrac distance (Lozupone and Knight 2005). All the diversity calculations were performed in QIIME.
Statistical analyses
One-way analysis of variance (ANOVA) followed by Tukey’s post-hoc HSD (Honest Significant Difference) was performed to identify differences in soil properties, the relative abundance of the major microbial phyla, Shannon index and phylogenetic diversity index among the three different soil layers. The relationships between the Shannon index and phylogenetic diversity index with soil physicochemical factors were tested by Spearman’s correlation analysis. All analyses were conducted using the SPSS 20.0 software (IBM Co., Armonk, NY, USA).
A permutation multivariate analysis of variance (PERMANOVA) was conducted to identify significant differences in community composition variance among soil layers. Venn diagrams for graphical descriptions of unique and shared bacterial genera between different soil layers were calculated using the “VennDiagram” package in R (Team RDC 2016). Nonmetric multidimensional scaling (NMDS) analysis based on the unweighted UniFrac distance matrix was conducted to identify variations in bacterial communities among soil layers using the nmds.py script in QIIME. Redundancy analysis (RDA) was employed to measure the effects of environmental variables on bacterial community structures in the CANOCO 4.5 software (Microcomputer Power, Ithaca, NY, USA). A Monte Carlo test (999 permutations) based on the RDA was used to assess the effects of each variable. We implemented a variation partitioning analysis to assess the relative importance of each factor (Distance factor: Latitude, Longitude; Environment factor: Temperature, Moisture, Salinity, TC, TN, TP, C/N, TOC, AN, AP, pH, Clay, Silt and Sand; Depth factor) in explaining the microbial community compositions with the “vegan” package in R.
Results
Soil physicochemical characterization
In general, soil properties changed with depth (Table 1). Soil temperature decreased sharply with depth, dropping from 6.27 °C in the active layer to −0.45 °C in the permafrost layer. The TC, TN and TP contents were all highest in the active layer. TC contents decreased significantly with depth and TN and TP contents decreased significantly from active layer to transition layer. Nevertheless, soil moisture and AP greatly increased with depth, reaching their maximum values in the permafrost layer. The soil was acidic, but the pH values did not vary significantly by depth. The distribution of clay, silt and sand did not vary significantly with depth. However, the soil salinity, C/N ratio, TOC content and AN value did not show obvious changes among depths.
Vertical distribution of soil bacterial communities
High-throughput Illumina sequencing yielded a total of 934,181 high-quality 16S rRNA gene sequences across all examined samples. The sequences were binned into 185,574 OTUs belonging to 63 phyla at 97% sequence identity. The microbial community composition was profiled according to their relative abundance at the phylum level (Fig. 2). Among those taxa examined, Proteobacteria (31.59%), Acidobacteria (18.63%), Bacteroidetes (9.74%), Chloroflexi (7.01%) and Actinobacteria (6.92%) were dominant, and these phyla accounted for > 70.95% of the bacterial sequences from all soils. Each sample also contained a number of sequences that could not be classified (5.19%), even at the phylum level. Although most bacterial groups were present in all samples, the relative abundances of the dominant bacterial taxa varied among soil depths. Overall, the abundance of Proteobacteria and Planctomycetes decreased significantly with soil depth, whereas Chloroflexi, Verrucomicrobia, Gemmatimonadetes, Crenarchaeota, Chlorobi and Firmicutes increased with depth.
The number of detected genera also varied across the three soil layers (Fig. 3). For example, a total of 957 genera were detected in the active layer, 910 in the transition layer and 872 in the permafrost layer. Overall, 132 unique genera were detected in the active layer, 56 in the transition layer and 58 in the permafrost layer. When the three soil layers were compared, we found that they shared 722 genera.
The bacterial community alpha-diversity based on the Shannon index and the phylogenetic diversity index both decreased significantly with soil depth (Fig. 4). Nonmetric multidimensional scaling (NMDS) analysis was performed to illustrate the bacterial community variance (beta-diversity) along soil layers (Fig. 5). Communities from the same soil layer tended to cluster together. Moreover, a PERMAVONA test based on the unweighted UniFrac distance matrix was performed to further test the significance of differences in microbial community composition between soil layers, and the results indicated that the composition of bacterial communities varied significantly among layers (PERMANOVA, P < 0.01).
Relationships between bacterial communities and environmental properties
The relative importance of each individual environmental variable on bacterial community composition was measured by redundancy analysis (Fig. 6). The first and second axis of the RDA explained 49.4% and 31.2% of the variance in the bacterial community, respectively. Of all soil properties examined, soil temperature (27.8%), TC (16.7%), TN (13.9%), TP (11.1%), soil moisture (8.3%) and clay content (5.6%) were the most significant factors underlying the variations in the bacterial community composition. Moreover, RDA ordination revealed distinct differences in bacterial community composition between soil layers. Bacterial communities of the active layer soils tended to be distributed in environments with high soil temperature and high TC, TN and TP contents, whereas bacterial communities of the permafrost layer soils were more concentrated in areas with high soil moisture and high clay content.
The effects of soil physicochemical factors on bacterial diversity were tested by Spearman’s correlation analysis (Table 2). The Shannon index was significantly positively correlated with soil temperature, TC, TN, TP, AN and sand content and negatively correlated with soil moisture, salinity, clay and silt content. The phylogenetic diversity index was significantly positively correlated with soil temperature, TC, TN, TP, AN, pH and sand content and negatively correlated with soil clay and silt content.
A variance partitioning analysis was carried out to assess the relative contributions of distance factor, environment factor and depth factor to microbial community composition (Fig. 7). The combination of these variables explained 45.92% of the observed variation in soil microbial community composition. Environmental factors explained the largest fraction of the variation (31.52%), with a pure effect of 17.59%. Depth factor and distance factor explained 21.22% and 4.59% of the variation, respectively.
Discussion
To our knowledge, this study provides a comprehensive comparison of patterns and drivers of bacterial communities among soil depth layers across the continuous permafrost region of Northeastern China. The dominant bacterial taxa phyla of Proteobacteria and Chloroflexi exhibited obvious changes in their relative abundance with soil depths (Fig. 2). The higher abundance of Proteobacteria and Planctomycetes in the active layer could be related to their preference for carbon- and nutrient-rich environments (higher TC, TN in the active layer, Table 1). This is in agreement with the studies in the Arctic (Saul et al. 2005) and on the Qinghai-Tibet Plateau (Zhang et al. 2017) reported that the predominant Proteobacteria comprised a higher percentage of the total bacterial population in carbon-rich soils. An important driver of species’ ecological functions differentiation is nutrient availability, leading to a spectrum of microbial lifestyles: at opposite ends, copiotrophs dominate in environments with greater nutritional opportunities, whereas oligotrophs prevalent in chronic starvation environments (Koch, 2001; Norris et al. 2021). The subdivision of Betaproteobacteria has been proposed as copiotrophs that prefer nutrient-rich environments (Fierer et al. 2007). Planctomycetes have large genomes that show features of copiotrophs based on genomic insight (Lauro et al. 2009). In the present study, Oligotrophic and anaerobic-like bacteria of Chloroflexi were more abundant in permafrost layers with relatively lower nutrient availability and higher soil moisture content (Table 1). This result is generally agreed with Fierer et al. (2012) reporting a decrease in relative abundance of Chloroflexi after N addition. Moreover, Chloroflexi were found to be well adapted to survive in a water-saturated permafrost wetland of Lake Namco (Yun et al. 2014). Because of their ability to resist long-term exposure to low temperatures and limited nutrient availability, Gemmatimonadetes, Chlorobi and the spore-forming Firmicutes have frequently been detected in deeper soil and permafrost (Debruyn et al. 2011; Wilhelmroland et al. 2011; Jansson and Taş 2014; Deng et al. 2015; Schostag et al. 2015). The observed abundance patterns could be related to the different resource availability of each bacterial group and suggest a close association with the corresponding soil conditions. Marked changes in soil parameters with depth have been found in this study (Table 1) and also in studies of other permafrost regions (Wu et al. 2012, 2017a; Dörfer et al. 2013), and such variations in soil properties are expected to influence the composition and diversity of bacterial communities inhabiting soils at different depths.
Our results showed that bacterial community structure and diversity showed obvious variations with soil depth in the studied region (Figs. 3, 4 and 5). Previous studies have indicated that microbial abundance and diversity were highest in the surface active layer soil and declined towards deeper layers to underlying permafrost soil (Yergeau et al. 2010; Wilhelmroland et al. 2011; Frankfahle et al. 2014; Koyama et al. 2014; Taş et al. 2014; Deng et al. 2015; Kim et al. 2016), and microbial community structures were significantly different between the active layer and the permafrost layer on the Tibetan Plateau (Hu et al. 2015, 2016) and in the Arctic (Steven et al. 2008; Mackelprang et al. 2011). Different environmental properties between soil depth layers could be responsible for the observed differences in microbial communities. The near-surface active layer experiences seasonal thawing and freezing and larger environmental fluctuations than permafrost, providing more probabilities for the growth of micro-organisms (Deng et al. 2015). In contrast, deeper soil layers are characterized by restraining factors of low temperature and limited oxygen and nutrient contents, which causes environmental stress to indigenous microorganisms and makes the layers less hospitable for microbial communities (Jansson and Taş 2014). Our results implied that the heterogeneous habitats might cause niche separation and subsequent variations in microbial communities between horizons.
Our results suggested that nutrient contents of TC, TN and TP had the greatest influence on both soil microbial community compositions (Fig. 6) and diversity patterns (Table 2) in the permafrost region of northeastern China. Previous studies have indicated that nutrient availability was strongly correlated with microbial mineralization and subsequently caused shifts in the bacterial community structure (Koyama et al. 2014; Siciliano et al. 2014; Deng et al. 2015). The predominant bacterial diversity in the active layer soil could be explained by their pre-adaption for the rapid metabolism of highly available nutrients (Fierer et al. 2003). Soil nutrient availability could also influence microbial communities via effects on the root exudates of plant communities (Millard and Singh 2010). Carbon and nitrogen concentrations were found to be related to microbial community compositions in permafrost affected soils on the Tibetan Plateau (Zhang et al. 2014). Significant correlations between microbial biomass and soil carbon contents with depth were also observed in terrestrial soils (Rumpel and Kögel-Knabner 2011; Eilers et al. 2012). Soil nitrogen levels played important roles both in the community structure of dominant bacteria and nitrogen-cycling communities in soils of the high Arctic and Antarctica (Walker et al. 2008; Ganzert et al. 2011). Moreover, phosphorus was reported to be an important growth-limiting soil nutrient affecting microbial community development and thus regulating microbial community structures (Siciliano et al. 2014; He et al. 2016). Soil microbial biomass increased in response to the addition of P in various soil environments (Griffiths et al. 2012; Liu et al. 2013). TP contents were highest in the active layer, whereas AP contents were highest in the permafrost layer in our study (Table 1). However, AP seemed to have no obvious effect on microbial richness (Table 2) and community structures (Fig. 6), suggesting that the form of phosphorus may play important roles in influencing microbial communities.
In the present study, soil temperature was found to be one of the main factors explaining the patterns observed in the bacterial community structure (Fig. 6), which was consistent with the results of earlier studies that identified temperature gradients along different soil depths as one of the primary environmental variables driving soil microbial community structure in other permafrost affected areas (Wagner et al. 2005; Yergeau et al. 2012). In accordance with many previous studies conducted in the Tibetan Plateau (Zhang et al. 2013; Yun et al. 2014), as well as in the Arctic and Antarctica (Fell et al. 2006; Bridge and Newsham 2009; Glanville et al. 2012; Lee et al. 2013; Steven et al. 2013), soil moisture was also found to make a great contribution to differentiation of bacterial community structure (Fig. 6). Soil moisture has been found to have important effects on soil respiration and oxygen availability (Wang et al. 2008; Yang et al. 2012), which influence bacterial community composition, especially that of carbon and nitrogen cycling bacteria (Høj et al. 2006; Zhang et al. 2013). The associated redox potential and anaerobic soil conditions in permafrost layers with high soil moisture have been shown to limit the diversity of bacterial community. Kim et al. (2008) found that short-term drought could lead to a dramatic decrease in gene abundance of the microbial community associated with greenhouse gas emissions. Interacting with other soil parameters, soil texture was shown to be an important factor influencing bacterial communities (Wu et al. 2017b). Although numerous studies have emphasized the importance of soil pH in driving soil microbial community structure (Chong et al. 2009, 2010; Feng et al. 2014; Siciliano et al. 2014), soil pH had no significant effect on the patterns of bacterial communities in our study. The low variability in pH among soil layers, which was not comparable to the influence of variables such as soil nutrient contents, temperature and moisture that spanned greater ranges, may explain this discrepancy with previous studies. Moreover, with 54.08% of unexplained variation in microbial community composition showed by variation partitioning analysis (Fig. 7), a more detailed consideration of a diverse set of environmental parameters is required in determining order to better understand the factors that drive microbial community structures in future studies.
According to the observed trend of climate warming, permafrost will thaw with the increase of ground temperature. And that will result in the enhancement of microbial activity and diversity, since soil temperature was positively correlated with microbial richness (Table 2). Besides, Planctomycetes and Proteobacteria, which showed higher abundance in the active layer (Fig. 2), are abundant in nitrogen-fixing populations involved in nitrogen cycling (Delmont et al. 2018). All of this could bring about huge positive feedback to the greenhouse effect and accelerate climate warming. Nevertheless, further research is required to reveal the detailed dynamics of carbon and nitrogen cycling with the corresponding measurement of microbial biomass and functional attributes of microbial communities in these changing permafrost habitats.
Conclusions
This study provides a comprehensive comparison of patterns and drivers of bacterial communities among different soil layers in the continuous permafrost region of northeastern China. Our results revealed significant differences in bacterial composition and diversity among the active layer, transition layer and permafrost layer. Our findings suggest that the heterogeneous environmental conditions between the three soil horizons had strong influences on microbial niche differentiation and further implied that soil nutrient contents, temperature and moisture predominantly explained the variability of soil bacterial community structures. This study improves our understanding of microbial ecology in this unique permafrost area, which is of great importance in assessment of spatial changes in permafrost ecosystems under current climate warming.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Abbreviations
- SDI:
-
Shannon diversity index
- PDI:
-
Phylogenetic diversity index
- TC:
-
Soil total carbon
- TN:
-
Soil total nitrogen
- TP:
-
Soil total phosphorus
- C/N:
-
Soil C:N
- TOC:
-
Soil total organic carbon
- AN:
-
Soil available nitrogen
- AP:
-
Soil available phosphorus
- ANOVA:
-
One-way analysis of variance
- QIIME:
-
Quantitative Insights into Microbial Ecology
- OTUs:
-
Operational taxonomic units
- PERMANOVA:
-
Permutation multivariate analysis of variance
- NMDS:
-
Nonmetric multidimensional scaling
- RDA:
-
Redundancy analysis
References
Aksenov AS, Shirokova LS, Kisil OY, Kolesova SN, Lim AG, Kuzmina D, Pouillé S, Alexis MA, Castrec-Rouelle M, Loiko SV, Pokrovsky OS (2021) Bacterial number and genetic diversity in a permafrost peatland (Western Siberia): testing a link with organic matter quality and elementary composition of a peat soil profile. Diversity 13(7):328
Bridge PD, Newsham KK (2009) Soil fungal community composition at Mars Oasis, a southern maritime Antarctic site, assessed by PCR amplification and cloning. Fungal Ecol 2:66–74
Chen YL, Deng Y, Ding JZ, Hu HW, Xu TL, Li F (2017) Distinct microbial communities in the active and permafrost layers on the tibetan plateau. Mol Ecol 26:6608–6620
Chong CW, Dunn MJ, Convey P, Tan GYA, Wong RCS, Tan IKP (2009) Environmental influences on bacterial diversity of soils on Signy Island, maritime Antarctic. Polar Biol 32:1571–1582
Chong CW, Pearce DA, Convey P, Tan GA, Wong RC, Tan IK (2010) High levels of spatial heterogeneity in the biodiversity of soil prokaryotes on Signy Island, Antarctica. Soil Biol Biochem 42:601–610
Dan D, Zhang DP, Liu WC, Lu CG, Zhang TT (2014) Diversity analysis of bacterial community from permafrost soil of Mo-he in China. Indian J Microbiol 54:111–113
Debruyn JM, Nixon LT, Fawaz MN, Johnson AM, Radosevich M (2011) Global biogeography and quantitative seasonal dynamics of gemmatimonadetes in soil. Appl Environ Microbiol 77:6295
Delmont TO, Quince C, Shaiber A, Esen ZC, Eren AM (2018) Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes. Nat Microbiol 3:804–813
Deng J, Gu Y, Zhang J, Xue K, Qin Y, Yuan M, Yin H, He Z, Wu L, Schuur EA (2015) Shifts of tundra bacterial and archaeal communities along a permafrost thaw gradient in Alaska. Mol Ecol 24:222
Doherty SJ, Barbato RA, Grandy AS, Thomas WK, Ernakovich JG (2020) The transition from stochastic to deterministic bacterial community assembly during permafrost thaw succession. Front Microbiol 11:596589
Dörfer C, Kühn P, Baumann F, He JS, Scholten T (2013) Soil organic carbon pools and stocks in permafrost-affected soils on the Tibetan Plateau. PLoS ONE 8:e57024
Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460
Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200
Eilers KG, Debenport S, Anderson S, Fierer N (2012) Digging deeper to find unique microbial communities: the strong effect of depth on the structure of bacterial and archaeal communities in soil. Soil Biol Biochem 50:58–65
Faith DP (1992) Conservation evaluation and phylogenetic diversity. Biol Cons 61:1–10
Fell JW, Scorzetti G, Connell L, Craig S (2006) Biodiversity of micro-eukaryotes in Antarctic Dry Valley soils with <5% soil moisture. Soil Biol Biochem 38:3107–3119
Feng Y, Grogan P, Caporaso JG, Zhang H, Lin X, Knight R, Chu H (2014) pH is a good predictor of the distribution of anoxygenic purple phototrophic bacteria in Arctic soils. Soil Biol Biochem 74:193–200
Fierer N, Schimel JP, Holden PA (2003) Variations in microbial community composition through two soil depth profiles. Soil Biol Biochem 35:167–176
Fierer N, Bradford MA, Jackson RB (2007) Toward an ecological classification of soil bacteria. Ecology 88:1354–1364
Fierer N, Lauber CL, Ramirez KS, Zaneveld J, Bradford MA, Knight R (2012) Comparative metagenomic, phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients. ISME J 6:1007
Frankfahle BA, Yergeau E, Greer CW, Lantuit H, Wagner D (2014) Microbial functional potential and community composition in permafrost-affected soils of the NW Canadian Arctic. PLoS ONE 9:e84761
Frey B, Rime T, Phillips M, Stierli B, Hajdas I, Widmer F, Hartmann M (2016) Microbial diversity in European alpine permafrost and active layers. FEMS Microbiol Ecol 92:fiw018
Ganzert L, Lipski A, Eacute HHW, Wagner D (2011) The impact of different soil parameters on the community structure of dominant bacteria from nine different soils located on Livingston Island, South Shetland Archipelago, Antarctica. FEMS Microbiol Ecol 76:476–491
Gibson J, Shokralla S, Porter TM, King I, van Konynenburg S, Janzen DH, Hallwachs W, Hajibabaei M (2014) Simultaneous assessment of the macrobiome and microbiome in a bulk sample of tropical arthropods through DNA metasystematics. Proc Natl Acad Sci 111:8007–8012
Glanville HC, Hill PW, Maccarone LD, Golyshin PN, Murphy DV, Jones DL (2012) Temperature and water controls on vegetation emergence, microbial dynamics, and soil carbon and nitrogen fluxes in a high Arctic tundra ecosystem. Funct Ecol 26:1366–1380
Graham DE, Wallenstein MD, Vishnivetskaya TA, Waldrop MP, Phelps TJ, Pfiffner SM, Onstott TC, Whyte LG, Rivkina EM, Gilichinsky DA (2012) Microbes in thawing permafrost: the unknown variable in the climate change equation. ISME J 6:709
Griffiths BS, Spilles A, Bonkowski M (2012) C:N:P stoichiometry and nutrient limitation of the soil microbial biomass in a grazed grassland site under experimental P limitation or excess. Ecol Process 1:6
He D, Xiang X, He JS, Wang C, Cao G, Adams J, Chu H (2016) Composition of the soil fungal community is more sensitive to phosphorus than nitrogen addition in the alpine meadow on the Qinghai-Tibetan Plateau. Biol Fertil Soils 52:1059–1072
Heslop JK, Winkel M, Walter Anthony KM, Spencer RG, Podgorski DC, Zito P, Kholodov A, Zhang M, Liebner S (2019) Increasing organic carbon biolability with depth in yedoma permafrost: ramifications for future climate change. J Geophys Res Biogeosci 124:2021–2038
Høj L, Rusten M, Haugen LE, Olsen RA, Torsvik VL (2006) Effects of water regime on archaeal community composition in Arctic soils. Environ Microbiol 8:984–996
Hu W, Zhang Q, Tian T, Li D, Cheng G, Mu J, Wu Q, Niu F, Stegen JC, An L (2015) Relative roles of deterministic and stochastic processes in driving the vertical distribution of bacterial communities in a permafrost core from the Qinghai-Tibet Plateau, China. PLoS ONE 10:e0145747
Hu W, Zhang Q, Tian T, Li D, Cheng G, Mu J, Wu Q, Niu F, An L, Feng H (2016) Characterization of the prokaryotic diversity through a stratigraphic permafrost core profile from the Qinghai-Tibet Plateau. Extremophiles 20:337–349
Jansson JK, Taş N (2014) The microbial ecology of permafrost. Nat Rev Microbiol 12:414
Jin H, Yu Q, Lü L, Guo D, He R, Yu S, Sun G, Li Y (2007) Degradation of permafrost in the Xing’anling Mountains, northeastern China. Permafrost Periglac Process 18:245–258
Kalra YP (1995) Determination of pH of soils by different methods. J AOAC Int 78:310–324
Kim SY, Lee SH, Freeman C, Fenner N, Kang H (2008) Comparative analysis of soil microbial communities and their responses to the short-term drought in bog, fen, and riparian wetlands. Soil Biol Biochem 40:2874–2880
Kim HM, Min JL, Ji YJ, Hwang CY, Kim M, Ro HM, Chun J, Lee YK (2016) Vertical distribution of bacterial community is associated with the degree of soil organic matter decomposition in the active layer of moist acidic tundra. J Microbiol 54:713
Koch AL (2001) Oligotrophs versus copiotrophs. BioEssays 23:657–661
Kong Y (2011) Btrim: a fast, lightweight adapter and quality trimming program for next-generation sequencing technologies. Genomics 98:152–153
Koyama A, Wallenstein MD, Simpson RT, Moore JC (2014) Soil bacterial community composition altered by increased nutrient availability in Arctic tundra soils. Front Microbiol 5:516
Lauro FM, Mcdougald D, Thomas T, Williams TJ, Egan S, Rice S, Demaere MZ, Ting L, Ertan H, Johnson J (2009) The genomic basis of trophic strategy in marine bacteria. Proc Natl Acad Sci USA 106:15527
Lee SH, Jang I, Chae N, Choi T, Kang H (2013) Organic layer serves as a hotspot of microbial activity and abundance in Arctic tundra soils. Microb Ecol 65:405
Liu L, Zhang T, Gilliam FS, Gundersen P, Zhang W, Chen H, Mo J (2013) Interactive effects of nitrogen and phosphorus on soil microbial communities in a tropical forest. PLoS ONE 8:e61188
Lozupone C, Knight R (2005) UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71:8228–8235
Mackelprang R, Waldrop MP, DeAngelis KM, David MM, Chavarria KL, Blazewicz SJ, Rubin EM, Jansson JK (2011) Metagenomic analysis of a permafrost microbial community reveals a rapid response to thaw. Nature 480:368–371
Millard P, Singh BK (2010) Does grassland vegetation drive soil microbial diversity? Nutr Cycl Agroecosyst 88:147–158
Norris N, Levine NM, Fernandez VI, Stocker R (2021) Mechanistic model of nutrient uptake explains dichotomy between marine oligotrophic and copiotrophic bacteria. Microbiology 17:e1009023
Ren B, Hu Y, Chen B, Zhang Y, Thiele J, Shi R, Liu M, Bu R (2018) Soil pH and plant diversity shape soil bacterial community structure in the active layer across the latitudinal gradients in continuous permafrost region of northeastern China. Sci Rep 8:5619
Rumpel C, Kögel-Knabner I (2011) Deep soil organic matter—a key but poorly understood component of terrestrial C cycle. Plant Soil 338:143–158
Sannino C, Borruso L, Mezzasoma A, Battistel D, Guglielmin M (2021) Abiotic factors affecting the bacterial and fungal diversity of permafrost in a rock glacier in the Stelvio Pass (Italian Central Alps). Appl Soil Ecol 166:104079
Saul DJ, Aislabie JM, Brown CE, Harris L, Foght JM (2005) Hydrocarbon contamination changes the bacterial diversity of soil from around Scott Base, Antarctica. FEMS Microbiol Ecol 53:141–155
Schostag M, Stibal M, Jacobsen CS, Bælum J, Taş N, Elberling B, Jansson JK, Semenchuk P, Priemé A (2015) Distinct summer and winter bacterial communities in the active layer of Svalbard permafrost revealed by DNA- and RNA-based analyses. Front Microbiol 6:399
Schuur EAG, McGuire AD, Schädel C, Grosse G, Harden JW, Hayes DJ, Hugelius G, Koven CD, Kuhry P, Lawrence DM, Natali SM, Olefeldt D, Romanovsky VE, Schaefer K, Turetsky MR, Treat CC, Vonk JE (2015) Climate change and the permafrost carbon feedback. Nature 520:171–179
Siciliano SD, Palmer AS, Winsley T, Lamb E, Bissett A, Brown MV, Dorst JV, Ji M, Ferrari BC, Grogan P (2014) Soil fertility is associated with fungal and bacterial richness, whereas pH is associated with community composition in polar soil microbial communities. Soil Biol Biochem 78:10–20
Steven B, Pollard WH, Greer CW, Whyte LG (2008) Microbial diversity and activity through a permafrost/ground ice core profile from the Canadian high Arctic. Environ Microbiol 10:3388–3403
Steven B, Lionard M, Kuske CR, Vincent WF (2013) High bacterial diversity of biological soil crusts in water tracks over permafrost in the High Arctic Polar Desert. PLoS ONE 8:e71489
Taş N, Prestat E, Mcfarland JW, Wickland KP, Knight R, Berhe AA, Jorgenson T, Waldrop MP, Jansson JK (2014) Impact of fire on active layer and permafrost microbial communities and metagenomes in an upland Alaskan boreal forest. ISME J 8:1904–1919
Team RDC (2016) R: a language and environment for statistical computing. Computing 1:12–21
Wagner D, Lipski A, Embacher A, Gattinger A (2005) Methane fluxes in permafrost habitats of the Lena Delta: effects of microbial community structure and organic matter quality. Environ Microbiol 7:1582–1592
Walker JK, Egger KN, Henry GH (2008) Long-term experimental warming alters nitrogen-cycling communities but site factors remain the primary drivers of community structure in high arctic tundra soils. ISME J 2:982
Walkley A (1947) A critical examination of a rapid method for determining organic carbon in soils-effect of variations in digestion conditions and of inorganic soil constituents. Soil Sci 63:251–264
Wang G, Li Y, Wang Y, Wu Q (2008) Effects of permafrost thawing on vegetation and soil carbon pool losses on the Qinghai-Tibet Plateau, China. Geoderma 143:143–152
Wei Z, Jin H, Zhang J, Yu S, Han X, Ji Y, He R, Chang X (2011) Prediction of permafrost changes in Northeastern China under a changing climate. Sci China Earth Sci 54:924–935
Wei S, Cui H, He H, Hu F, Su X, Zhu Y (2014) Diversity and distribution of archaea community along a stratigraphic permafrost profile from Qinghai-Tibetan Plateau, China. Archaea Int Microbiol J 2014:240817
Werner JJ, Koren O, Hugenholtz P, DeSantis TZ, Walters WA, Caporaso JG, Angenent LT, Knight R, Ley RE (2012) Impact of training sets on classification of high-throughput bacterial 16S rRNA gene surveys. ISME J 6:94–103
Wilhelmroland C, Niederbergerthomas D, GreerCharles C, Whytelyle G (2011) Microbial diversity of active layer and permafrost in an acidic wetland from the Canadian High Arctic. Can J Microbiol 57:303
Wu X, Lin Z, Chen M, Fang H, Yue G, Ji C, Pang Q, Wang Z, Ding Y (2012) Soil organic carbon and its relationship to vegetation communities and soil properties in permafrost areas of the central western Qinghai-Tibet Plateau, China. Permafrost Periglac Process 23:162–169
Wu X, Fang H, Zhao Y, Smoak JM, Li W, Shi W, Sheng Y, Zhao L, Ding Y (2017a) A conceptual model of the controlling factors of soil organic carbon and nitrogen densities in a permafrost-affected region on the eastern Qinghai-Tibetan Plateau. J Geophys Res Biogeosci 122:1705
Wu X, Xu H, Liu G, Ma X, Mu C, Zhao L (2017b) Bacterial communities in the upper soil layers in the permafrost regions on the Qinghai-Tibetan plateau. Appl Soil Ecol 120:81–88
Wu X, Zhao L, Liu G, Xu H, Zhang X, Ding Y (2018) Effects of permafrost thaw-subsidence on soil bacterial communities in the southern Qinghai-Tibetan Plateau. Appl Soil Ecol 128:81–88
Yang S, Wen X, Jin H, Wu Q (2012) Pyrosequencing investigation into the bacterial community in permafrost soils along the China-Russia crude oil pipeline (CRCOP). PLoS ONE 7:e52730
Yergeau E, Hogues H, Whyte LG, Greer CW (2010) The functional potential of high Arctic permafrost revealed by metagenomic sequencing, qPCR and microarray analyses. ISME J 4:1206–1214
Yergeau E, Bokhorst S, Kang S, Zhou J, Greer CW, Aerts R, Kowalchuk GA (2012) Shifts in soil microorganisms in response to warming are consistent across a range of Antarctic environments. ISME J 6:692
Yun J, Ju Y, Deng Y, Zhang H (2014) Bacterial community structure in two permafrost wetlands on the Tibetan Plateau and Sanjiang Plain, China. Microb Ecol 68:360–369
Zhang XF, Zhao L, Xu SJ, Liu YZ, Liu HY, Cheng GD (2013) Soil moisture effect on bacterial and fungal community in Beilu River (Tibetan Plateau) permafrost soils with different vegetation types. J Appl Microbiol 114:1054–1065
Zhang X, Xu S, Li C, Lin Z, Feng H, Yue G, Ren Z, Cheng G (2014) The soil carbon/nitrogen ratio and moisture affect microbial community structures in alkaline permafrost-affected soils with different vegetation types on the Tibetan plateau. Res Microbiol 165:128
Zhang B, Wu X, Zhang G, Zhang W, Liu G, Chen T, Qin Y, Zhang B, Sun L (2017) Response of soil bacterial community structure to permafrost degradation in the upstream regions of the Shule River Basin, Qinghai-Tibet Plateau. Geomicrobiol J 34:300–308
Zhou X, Zhang Z, Tian L, Li X, Tian C (2017) Microbial communities in peatlands along a chronosequence on the Sanjiang Plain, China. Sci Rep 7:9567
Zhou L, Zhou Y, Yao X, Cai J, Jeppesen E (2020) Decreasing diversity of rare bacterial subcommunities relates to dissolved organic matter along permafrost thawing gradients. Environ Int 134:105330
Acknowledgements
We are grateful to all the members of our team for the fieldwork.
Funding
This study was supported by the National Basic Research Program of China (973 program, 2013CBA01807) and the National Natural Science Foundation of China (32001127).
Author information
Authors and Affiliations
Contributions
BR, YH and RB designed this study; BR performed the laboratory analysis and wrote the paper. All authors read and approve the final manuscript.
Corresponding author
Ethics declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Ren, B., Hu, Y. & Bu, R. Vertical distribution patterns and drivers of soil bacterial communities across the continuous permafrost region of northeastern China. Ecol Process 11, 6 (2022). https://doi.org/10.1186/s13717-021-00348-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1186/s13717-021-00348-8