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Article

Elevational Patterns and Environmental Drivers of Dominant Bacterial Communities in Alpine Forest Soils of Mt. Taibai, China

by
Zhigang Li
1,
Xin Wei
2 and
Yanbing Qi
1,*
1
College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China
2
College of Humanities and Social Development, Northwest A&F University, Yangling 712100, China
*
Author to whom correspondence should be addressed.
Forests 2025, 16(5), 814; https://doi.org/10.3390/f16050814
Submission received: 8 April 2025 / Revised: 6 May 2025 / Accepted: 12 May 2025 / Published: 14 May 2025
(This article belongs to the Section Forest Soil)
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Abstract

:
Alpine ecosystems, as one of the most representative terrestrial ecosystems, have garnered significant attention due to their susceptibility to human activities and climate change. However, the distribution patterns and driving factors of alpine soil bacterial communities remain to be further explored, especially for different dominant phyla. This study investigated the soil bacterial community composition, elevational patterns, and relationships between bacterial diversity and environmental factors at four elevation gradients (2406–3204 m) on Mt. Taibai, Qinling Mountains, China, using 16S rRNA sequencing. The results showed that the dominant bacterial phyla were Acidobacteria, Actinobacteria, Proteobacteria, and Chloroflexi, accounting for over 69% of the bacterial sequences in soil samples. Dominant bacterial communities exhibit distinct elevation gradient patterns in diversity and community structure. The α-diversity of Actinobacteria and Chloroflexi decreases with increasing elevation, whereas that of Proteobacteria and Acidobacteria increases. Moreover, the community structure of Actinobacteria shows greater variation across elevations than the other three dominant bacterial groups, with significant differences observed among elevations. Redundancy analysis and distance decay analysis revealed that elevation was significantly correlated with the soil bacterial community structure (p < 0.01). Different dominant bacterial communities were regulated by distinct environmental factors, providing strong evidence for understanding microbial community assembly. Therefore, the α- and β-diversity of soil bacteria on Mt. Taibai exhibit distinct elevational variations, and elevation-driven plant diversity and pH may be key factors shaping the spatial distribution of soil bacteria.

1. Introduction

Elevational gradients serve as natural laboratories for studying microbial biogeography due to their pronounced environmental variations over short spatial scales. Soil microorganisms play a crucial role in ecosystem functioning, particularly in nutrient cycling, organic matter decomposition, and soil fertility maintenance [1]. Previous studies have shown a significant positive correlation between soil microbial diversity and ecosystem multifunctionality [2,3,4]. Therefore, understanding their distribution along elevational gradients is essential for predicting ecosystem responses to climate change and human disturbances. However, despite the growing body of research on microbial diversity in mountain ecosystems, studies on the biogeographical distribution patterns of dominant microbial communities and their driving factors along elevational gradients remain insufficient. Different microbial groups may be influenced by different environmental factors and exhibit inconsistent responses to climate change and human activities. Elucidating the elevational variation characteristics of different microbial taxa is of great significance for microbial community management and climate change mitigation.
Numerous studies have explored how soil microbial diversity and composition change along elevational gradients, revealing that microbial communities are influenced by multiple environmental factors, including abiotic factors, such as soil pH, temperature, and moisture, as well as biotic factors, such as vegetation composition [5,6,7,8,9,10]. The α-diversity of soil microorganisms typically exhibits hump-shaped, decreasing, or relatively stable trends with increasing elevation, depending on specific environmental conditions and microbial taxa [11,12,13,14]. In mountain soils, Acidobacteria, Actinobacteria, Proteobacteria, and Chloroflexi are generally dominant [13,14], with their relative abundances shifting along elevational gradients. Soil pH, organic carbon content, and plant diversity are widely recognized as key factors shaping microbial community structure [15,16,17,18]. In fact, different microbial taxa exhibit varying responses to elevation changes, particularly within the dominant bacterial communities. For example, increased temperature significantly impacts soil microbial diversity and alters the relative abundances of Actinobacteria, Bacteroidetes, and Proteobacteria [19]. Therefore, the focus should be on the distribution patterns and driving factors of specific bacterial phyla rather than solely on the entire microbial community.
Although broad taxonomic groups have been studied, the elevational distribution patterns of specific dominant bacterial genera remain unclear. Additionally, the mechanisms driving microbial community shifts along elevational gradients require further investigation. Alpine forest ecosystems are sensitive to climate change, which causes the upper altitude limit of trees to continue to move upward, affecting the soil bacterial community and structure. To fill this knowledge gap, this study focuses on Mt. Taibai, the highest peak of the Qinling Mountains, to explore the biogeographical distribution patterns of major dominant soil bacterial communities in alpine forest ecosystems. Investigating the variations in soil microbial diversity along the elevation gradient of Taibai Mountain can help elucidate microbial responses to environmental factors, enhance our understanding of mountain ecosystem functions, and provide scientific support for ecological management under global climate change.
We hypothesize that (H1) soil bacterial α-diversity declines with increasing elevation due to decreasing temperature and fluctuating pH; (H2) the relative abundances of dominant bacterial phyla (e.g., Proteobacteria, Actinobacteria, Acidobacteria) vary with elevation and are driven by specific environmental factors; and (H3) soil pH, temperature, and organic matter content are key regulators of bacterial β-diversity and community structure along elevational gradients. This study will employ high-throughput sequencing combined with soil physicochemical analysis to systematically investigate soil microbial diversity and its driving mechanisms along the elevation gradient of Taibai Mountain, providing scientific insights into microbial ecological processes in mountain ecosystems.

2. Materials and Methods

2.1. Study Site

The Qinling Mountains are not only highly sensitive to global climate change [20,21] but they also exhibit a typical vertical distribution of vegetation zones, with Taibai Mountain being an optimal site for studying the vertical changes in soil bacterial communities in alpine forest ecosystems, as well as being a prime location for investigating the changes in soil dominant taxa and their influencing factors along the altitudinal gradient.
The study area is located on Taibai Mountain, Qinling, Meixian County, Shaanxi Province, China (107°19′–107°58′ E, 33°49′–34°10′ N). The Qinling Mountains serve as the natural boundary between northern and southern China. The mountain exhibits vertical zonation across warm temperate, temperate, cold temperate, and alpine climatic zones. The mean annual temperature (MAT) ranges from 11.0 °C at 1250 m to 1.1 °C at 3250 m, while the mean annual precipitation (MAP) varies between 600 and 1000 mm, peaking at mid-elevations (1850–2400 m). These diverse environmental factors have led to the formation of various forest types along the altitudinal gradient (Figure 1) [6]. In the alpine forest zone of Taibai Mountain (above 2000 m), soil types change with elevation: gray-brown soil (1500–2800 m), podzolic soil (2800–3000 m), and alpine meadow soil (above 3000 m) [22].

2.2. Sample Collection

Soil samples at different elevation gradients were collected in August 2023. Soil samples were collected at elevations of 2406, 2809, 3044, and 3204 m on Taibai Mountain, Qinling Mountains. We selected 6 sampling points at each elevation, and each sampling point included three 20 × 20 m sample plots. Vegetation surveys were conducted in each sample plot to calculate plant diversity. Soils from 5 to 10 trees per plot were composited to form one replicate sample per sampling point, and plants, such as surface plant litter, were peeled off to collect soil in the rhizosphere area of the plants. As the soil layer is typically shallow (<20 cm), root systems are concentrated near the surface. We collected 0–5 cm of soil and mixed the soil of each tree to obtain a comprehensive sample at each sampling point. Four elevations, 6 soil samples at each elevation, and a total of 24 samples were obtained. After the samples were collected, the soil samples were divided into three parts: one-third of each soil sample was stored at 4 °C for the analysis of nitrate and ammonium nitrogen; one-third was stored at −80 °C for microbial DNA extraction; and the remaining one-third was air-dried for the determination of pH, available phosphorus, and organic matter.

2.3. Analysis of Basic Soil Properties

The basic properties of soils at different elevation gradients were analyzed according to the general method [23]. Specifically, soil pH was extracted with 1M KCl, the soil–water ratio was 1:5, and the pH of the extract was measured by a glass electrode. The soil available phosphorus (AVP) content was extracted with 0.5M NaHCO3, and the phosphorus content in the extract was measured by molybdenum antimony colorimetry [24,25]. The fresh soil used for the determination of soil nitrate nitrogen (NO3⁻-N) and ammonium nitrogen (NH4+-N) was extracted with 1M KCl, and the nitrate nitrogen content in the extract was measured by spectrophotometry [23,26,27]. Soil organic matter was obtained by air-drying soil that had passed through a 100-mesh sieve. The organic carbon content in the soil was determined using the potassium dichromate external heating method, and the soil organic matter (SOM) content was obtained using a conversion factor of 1.724 [28].

2.4. High-Throughput Sequencing and Data Analysis

Soil DNA was extracted using a DNA-specific kit (MoBio Laboratories, Carlsbad, CA, USA), and the extraction steps were strictly carried out in accordance with the instructions. The purity and concentration of the extracted DNA were determined, and then it was amplified using PCR. To amplify the 16S rRNA V3-V4 variable region, the universal primers (338F: ACTCCTACGGGAGGCAGCA and 806R:GGACTACHVGGGTWTCTAAT) were employed [29]. The PCR reaction system consisted of 13 μL H2O, 10 μL Mix, 0.5 μL of 10 μM forward primer, 0.5 μL reverse primer, and 1.0 μL DNA. The amplification program was as follows: initial denaturation at 94 °C for 3 min, followed by 35 cycles of denaturation at 94 °C for 45 s, annealing at 50 °C for 60 s, and extension at 72 °C for 90 s, with a final extension at 72 °C for 10 min [30]. The amplification products were purified and pooled for the following sequencing with an Illumina HiSeq 2500 platform at Shanghai Personal Biotechnology Co., Ltd. (Shanghai, China).
The sequencing data were processed using DADA2 [31], including primer removal, quality filtering, sequence merging, and ASV clustering. After taxonomic annotation, we analyzed bacterial community α- and β-diversity to explore soil bacterial distribution patterns across elevation gradients. α-diversity was assessed using the Shannon index and species richness (observed species count), while principal coordinate analysis (PCoA) examined variations in bacterial community structure along elevations. Redundancy analysis (RDA) was conducted to evaluate the effects of elevation, vegetation, and soil properties on bacterial community composition. A random forest model was applied to determine the influence of environmental factors on bacterial α-diversity (Shannon index) and community structure, with significance testing. To further investigate elevation-driven shifts in dominant bacterial communities, we separately analyzed the major phyla Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi, assessing their α-diversity and community composition along the gradient. Additionally, a Mantel test was used to quantify environmental influences on these dominant bacterial groups. All analyses were performed in R 4.3.1 using the microeco package [32].
Differences in soil properties and bacterial α-diversity were analyzed using ANOVA at the 0.05 significance level. Prior to ANOVA, data were tested for homogeneity of variance, and non-parametric tests were applied to data that did not meet the assumptions of normality. To quantify the relative contributions of mean annual temperature (MAT) and soil properties to soil bacterial composition on Taibai Mountain, Variance Partitioning Analysis (VPA) was performed using the “vegan 2.6-10” package [33]. This analysis separately calculated the relative influence of temperature and fundamental soil properties on the dominant bacterial communities. Since MAT was derived using an empirical formula, the effect of elevation was not independently discussed. Elevation serves as a composite factor that integrates multiple environmental variables, including temperature, precipitation, vegetation, and solar radiation. To assess changes in the dominant bacterial phyla across different elevation gradients, depth decay was determined using linear regression between bacterial community composition similarity and elevation distance.

3. Results

3.1. Changes in Soil Properties Along Altitudinal Gradients

Significant differences were observed in basic soil physicochemical properties across different elevations (Table 1). High-elevation soils exhibited higher pH and organic matter content, whereas plant diversity was significantly greater at lower elevations. Soil pH varied between 4.88 and 5.01, with higher values observed at higher elevations. Organic matter decreased from 2406 m to 2809 m, then increased sharply at 3204 m, perhaps due to slower decomposition rates or reduced leaching. Available phosphorus content exhibited a fluctuating pattern, initially increasing with elevation, then decreasing, and subsequently increasing again. Soils at higher elevations may exhibit higher pH and organic matter content, possibly due to slower decomposition rates or reduced leaching.

3.2. Changes in Overall Soil Bacterial α-Diversity and β-Diversity

The variation in soil bacterial α-diversity across different elevations was assessed using the Shannon index and ASV richness (number of observed ASVs). Across the four sampled elevations, the Shannon index ranged from 7.27 to 7.67, while ASV richness varied between 4155 and 5149 (Figure 2). Notably, from 2406 m to 3204 m, the Shannon index exhibited a significant upward trend with increasing elevation (p < 0.05). The lowest Shannon index was recorded at 2406 m, which was significantly lower than at other elevations. However, no significant differences in either the Shannon index or ASV richness were observed between 2809 m and 3204 m.
At the phylum level, the dominant bacterial taxa in the soil included Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi, collectively accounting for 69.5%–80.3% of the total bacterial community (Figure 3). Elevation significantly influenced the relative abundance of these dominant bacterial phyla (p < 0.05). Specifically, at 2406 m, Proteobacteria (28.2%) and Actinobacteria (31.3%) were the most abundant phyla. At 2809 m, Proteobacteria (26.5%) and Acidobacteria (23.5%) dominated. At 3044 m, Proteobacteria (28.2%), Actinobacteria (18.8%), and Acidobacteria (20.2%) were the most prevalent, while at 3204 m, Proteobacteria (35.1%) and Acidobacteria (17%) were dominant.
At the order level, Rhizobiales and Burkholderiales were the most dominant taxa, together accounting for 17.4%–23.7% of the total bacterial community. However, their distribution patterns along the elevation gradient differed. Rhizobiales were more prevalent at lower elevations (A1: 2406 m), whereas Burkholderiales exhibited higher abundance at higher elevations (A4: 3204 m). The ANOVA results indicated that the relative abundance of Rhizobiales at 2406 m was significantly higher than at other elevations (p < 0.05), with no significant differences observed between 2809 m and 3204 m. In contrast, the relative abundance of Burkholderiales at 3204 m was significantly higher than at other elevations (p < 0.05), while no significant differences were found between 2406 m and 3044 m.

3.3. Variation in α-Diversity and β-Diversity of Dominant Soil Bacterial Communities

The α-diversity indices of the major dominant bacterial communities exhibited significant variation along the elevation gradient (Figure 4). The richness of Proteobacteria and Acidobacteria increased significantly with elevation, whereas Actinobacteria and Chloroflexi showed a decreasing trend. Overall, the diversity of Proteobacteria and Acidobacteria was higher than that of Actinobacteria and Chloroflexi.
The community structure of dominant bacterial taxa also varied substantially across elevations (Figure 5). Among them, Actinobacteria exhibited the most pronounced structural differences, with samples from different elevations clustering separately, indicating a strong influence of elevation on Actinobacteria communities. The community structures of Acidobacteria, Proteobacteria, and Chloroflexi also exhibited distinct elevation-related variations, with samples from lower elevations (2406–2809 m) being clearly distinguishable from those at higher elevations (2809–3204 m).

3.4. Key Environmental Factors Regulating Soil Bacterial Communities

To identify the key environmental variables shaping soil bacterial community structure, redundancy analysis (RDA) was performed. The first axis explained 35.8% of the variation, while the second axis accounted for 18.9%. The Shannon indices of plant diversity, elevation, and soil pH were identified as the most critical environmental factors influencing bacterial community composition (Figure 6). Random forest model analysis further confirmed that elevation and plant diversity were the primary drivers of both soil bacterial α- and β-diversity. Specifically, these environmental variables explained 30.03% of the variation in bacterial α-diversity, while 76.18% of the variation in β-diversity was attributed to them, indicating that β-diversity was more strongly shaped by these variables than α-diversity.
Elevation exerted a significant impact on the β-diversity of dominant bacterial phyla (Figure 7). Regression analysis revealed that the Bray–Curtis distances of Proteobacteria (R = 0.68), Actinobacteria (R = 0.563), Acidobacteria (R = 0.447), and Chloroflexi (R = 0.315) were significantly correlated with the Euclidean distance of elevation (p < 0.001), indicating that Proteobacteria showed the strongest correlation with elevation, suggesting higher sensitivity compared to other phyla.
The Mantel test further revealed that different dominant bacterial communities were influenced by distinct environmental factors (Figure 8). Specifically, Proteobacteria and Actinobacteria were primarily regulated by elevation, soil pH, available phosphorus, and plant diversity (p < 0.05). Acidobacteria were mainly influenced by elevation and pH, whereas Chloroflexi were affected by elevation, pH, available phosphorus, and plant community composition.
Different bacterial phyla exhibited inconsistent responses to elevation and soil properties. To further assess the relative contributions of mean annual temperature (MAT) and soil properties to the variation in dominant bacterial communities, variation partitioning analysis was conducted (Figure 9). The results indicated that temperature had a greater impact on Actinobacteria and Proteobacteria than on Acidobacteria and Chloroflexi. For Chloroflexi, the influence of MAT (8%) was lower than that of soil factors (14%). In contrast, for Proteobacteria, temperature and soil properties accounted for 12% and 9% of the variation, respectively.

4. Discussion

Elevation is a major driving factor influencing the biogeographical distribution of flora and fauna [34,35]. In recent years, the elevation-related distribution patterns of soil microbial communities have also been gradually revealed. Previous studies have shown that compared to plants, the altitudinal distribution patterns of bacterial and fungal communities in soil are less distinct [36]. However, most existing research has primarily focused on the overall soil bacterial community, often overlooking variations at the community scale. Different microbial communities exhibit varied responses to environmental factors. For instance, elevation significantly alters plant community composition, which in turn directly influences soil bacterial communities, particularly functional bacteria involved in organic matter decomposition. Additionally, variations in mean annual temperature across elevations affect microbial growth and metabolism [37], leading to shifts in bacterial community composition. Consequently, while elevation may have a relatively minor impact on overall bacterial diversity, it exerts a long-term influence on the diversity and composition of specific bacterial communities, ultimately shaping mountain soil ecosystem functions.

4.1. Effect of Elevation Change on the Diversity of Soil Microbial Communities

Contrary to commonly observed declines or non-significant trends, our findings demonstrate an increase in soil bacterial α-diversity with elevation in Mt. Taibai, highlighting a region-specific response. However, previous findings reported a significant decline in bacterial community diversity with increasing elevation [11,38], a U-shaped pattern [39], or no correlation between bacterial α-diversity and elevation [14]. The primary reason for these variations in altitudinal trends lies in differences in elevation ranges, habitats, and vegetation types. For example, in the eastern flank of the Andes, soil bacterial diversity monotonically decreases with increasing elevation, with temperature identified as the major driver of this diversity gradient, while soil properties, including pH, play a lesser role [40]. In contrast, in the Sygera Mountains, the α-diversity of soil bacterial communities did not show significant changes with elevation [14]. However, in Dongling Mountain, bacterial richness increased with elevation [12], which is consistent with the findings of this study. Moreover, while some studies have reported a decreasing trend in soil bacterial diversity with elevation, reports of increasing bacterial diversity estimated using the Shannon–Wiener index are rare. Theoretically, microbial communities in high-elevation regions experience extreme environmental stress due to arid conditions, low temperatures, and severe nutrient limitations, which reduce microbial activity and, consequently, lower microbial diversity [41].
Elevation influences bacterial community diversity primarily by affecting plant diversity and various environmental factors. For instance, elevation directly affects plant species distribution and diversity. In Mt. Taibai, plant diversity gradually decreases with increasing elevation, whereas soil bacterial diversity increases—an inverse trend that contradicts many previous studies. Although some studies have reported weak associations between plant and bacterial diversity [42], our data suggest taxon-specific responses, with Chloroflexi and Actinobacteria decreasing, while Acidobacteria and Proteobacteria increase with plant diversity (Figure 10). The relationship between plant diversity and soil bacterial diversity varies greatly, likely because different bacterial groups respond differently to changes in plant diversity [43,44]. These contrasting responses among bacterial groups alter the overall variation in soil bacterial diversity.
Previous studies have identified soil pH as the most critical environmental factor driving soil bacterial distribution and community structure [45,46]. Despite being a well-known driver, soil pH had limited influence on bacterial α-diversity in our study, likely due to a narrow pH range (~0.3 units). Research suggests that when soil pH varies widely, its impact on soil bacteria is more pronounced [47,48]. Since the optimal pH range for soil bacteria is relatively narrow and they are highly sensitive to pH changes [49], if the soil pH variation among sampling sites at different elevations is minimal, then fundamental soil properties, temperature, and other environmental factors may become the key drivers of soil bacterial community diversity. Additionally, apart from a significant negative correlation between soil ammonium nitrogen content and bacterial α-diversity, soil organic matter, nitrate, and available phosphorus showed no significant correlation with bacterial diversity, which contradicts previous studies. This suggests that in this region, plant factors and temperature variations driven by elevation primarily influence soil bacterial diversity. Studies have shown that temperature is a key factor affecting soil microbial diversity across different elevations [50]. These results underscore the importance of elevation-induced temperature variation as a primary ecological filter shaping bacterial diversity in mountainous environments.

4.2. Effect of Elevation Change on Soil Microbial Community Structure

Significant shifts in the relative abundance of dominant bacterial phyla along the elevational gradient indicate clear community structure differentiation in Mt. Taibai forest soils. The dominant bacterial phyla were Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi, which is consistent with previous studies showing that these microbial groups are widely distributed in various soils [26,47,51]. The significant variation in soil bacterial composition across elevations indicates that bacterial phyla in this study region are sensitive to altitudinal changes.
The dominance of Proteobacteria at higher elevations may reflect their metabolic versatility and cold-adaptive traits, such as enhanced membrane fluidity and psychrotolerance. This finding was further confirmed by variation partitioning analysis (VPA), which indicated that temperature had a greater influence on Proteobacteria than soil properties. As previous studies have suggested, microclimatic conditions are expected to play a crucial role in shaping the elevational distribution patterns of soil bacteria [50]. In contrast, Actinobacteria were more abundant in low-elevation areas, primarily involved in the decomposition of soil organic matter, with consistently high relative abundance across all elevations, highlighting their crucial role in soil carbon and nitrogen cycling. Previous studies have classified Acidobacteria as acidophilic bacteria that are better adapted to acidic soils [52] and highly sensitive to pH changes [53]. Although Acidobacteria are traditionally regarded as pH sensitive, our findings suggest that pH may influence their community composition more than their overall abundance. The distinct elevation-driven patterns observed among these dominant bacterial phyla indicate strong climatic niche differentiation within the soil bacterial community. Temperature not only directly influences microbial activity but also indirectly affects it by altering the community’s temperature dependence [54]. As a result, soil bacterial communities exhibit distinct variations across different elevations, with pronounced responses to temperature fluctuations.
Interestingly, while soil pH did not affect overall bacterial α-diversity, it significantly influenced the community structure of key bacterial phyla, indicating a compositional shift rather than a richness change. Mantel tests showed that pH significantly influenced the community structures of Acidobacteria, Proteobacteria, Actinobacteria, and Chloroflexi, emphasizing its critical role in shaping bacterial community composition. As previous studies have shown, pH regulates soil bacterial community structure and influences community composition [55,56]. Additionally, soil available phosphorus (AVP) had a significant effect on the community structures of Proteobacteria, Actinobacteria, and Chloroflexi, but not on Acidobacteria. Phosphate-solubilizing bacteria (PSB) within Proteobacteria and Actinobacteria may be particularly responsive to AVP availability, reflecting their functional roles in phosphorus cycling and microbial community adaptation under nutrient-limited conditions, as low phosphorus levels promote PSB growth, while excessive phosphorus inhibits their proliferation [57]. In natural ecosystems, phosphorus, essential for plant and microbial growth, mainly originates from the mineralization of soil organic phosphorus, with phosphate-solubilizing bacteria playing a crucial role in this process. Therefore, soil bacterial communities are significantly affected by soil available phosphorus.

5. Conclusions

Using 16S rRNA Illumina sequencing technology, we analyzed soil bacterial diversity and richness patterns along the elevational gradient of Mt. Taibai in the Qinling Mountains. The dominant bacterial phyla were Acidobacteria, Actinobacteria, Proteobacteria, and Chloroflexi, collectively accounting for more than 69% of the bacterial sequences. Overall bacterial diversity significantly increased with elevation from 2406 m to 2809 m (p < 0.01) and remained stable between 2809 m and 3204 m. Different bacterial communities exhibited distinct variation patterns along the elevational gradient. Bacterial community similarity indicated that high-altitude sites shared similar community structures, corresponding with patterns in vegetation type variation. Dominant bacterial phyla exhibited distinct and often opposing responses to elevational changes. Mantel tests and redundancy analysis (RDA) indicated that plant diversity and soil pH, driven by elevation, were likely the key factors shaping soil bacterial community structure and diversity on Mt. Taibai. Different dominant bacteria respond inconsistently to altitude, which has important implications for using microorganisms to cope with climate change and cultivate a healthy microbiome.

Author Contributions

Conceptualization, X.W. and Y.Q.; Methodology, Z.L.; Investigation, Z.L.; Writing—original draft, Z.L. and Y.Q.; Writing—review & editing, X.W. and Y.Q. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Foundation of China, 42277310.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

We are also grateful to Shanghai Personal Biotechnology Company for providing Illumina MiSeq sequencing and assisting in data analysis. We sincerely thank the reviewers for their constructive comments and hard work.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Hartmann, M.; Six, J. Soil structure and microbiome functions in agroecosystems. Nat. Rev. Earth Environ. 2023, 4, 4–18. [Google Scholar] [CrossRef]
  2. Luo, M.; Jia, X.; Zhao, Y.; Ye, X.; Ren, K.; Mu, Q.; Kang, S.; Wang, H.; Li, J. Spatial variations of the relationships between bacterial diversity and forest ecosystem multifunctionality in the Qinling Mountains, China. Appl. Soil Ecol. 2024, 203, 105638. [Google Scholar] [CrossRef]
  3. Hu, M.; Sardans, J.; Sun, D.; Yan, R.; Wu, H.; Ni, R.; Peñuelas, J. Microbial diversity and keystone species drive soil nutrient cycling and multifunctionality following mangrove restoration. Environ. Res. 2024, 251, 118715. [Google Scholar] [CrossRef] [PubMed]
  4. Shi, X.; Wang, J.; Lucas-Borja, M.E.; Wang, Z.; Li, X.; Huang, Z. Microbial diversity regulates ecosystem multifunctionality during natural secondary succession. J. Appl. Ecol. 2021, 58, 2833–2842. [Google Scholar] [CrossRef]
  5. Shen, C.; Shi, Y.; Fan, K.; He, J.-S.; Adams, J.M.; Ge, Y.; Chu, H. Soil pH dominates elevational diversity pattern for bacteria in high elevation alkaline soils on the Tibetan Plateau. FEMS Microbiol. Ecol. 2019, 95, fiz003. [Google Scholar] [CrossRef]
  6. Tian, Q.; Jiang, Q.; Huang, L.; Li, D.; Lin, Q.; Tang, Z.; Liu, F. Vertical distribution of soil bacterial communities in different forest types along an elevation gradient. Microb. Ecol. 2023, 85, 628–641. [Google Scholar] [CrossRef]
  7. Yang, N.; Li, X.; Liu, D.; Zhang, Y.; Chen, Y.; Wang, B.; Hua, J.; Zhang, J.; Peng, S.; Ge, Z. Diversity patterns and drivers of soil bacterial and fungal communities along elevational gradients in the Southern Himalayas, China. Appl. Soil Ecol. 2022, 178, 104563. [Google Scholar] [CrossRef]
  8. Vélez-Martínez, G.A.; Reyes-Ardila, W.L.; Duque-Zapata, J.D.; Rugeles-Silva, P.A.; Muñoz Flórez, J.E.; López-Álvarez, D. Soil bacteria and fungi communities are shaped by elevation influences in Colombian forest and páramo natural ecosystems. Int. Microbiol. 2024, 27, 377–391. [Google Scholar] [CrossRef]
  9. Chen, L.-F.; Kong, J.-Q.; He, Z.-B.; Zhao, W.-Z.; Song, M.-D.; Li, Y.-M.; Gao, Y.; Yang, S.-P. A fundamental role of slope aspect and elevation in controlling diversity patterns of soil bacterial communities: Insights from an arid-montane ecosystem in China. J. Soil Sci. Plant Nutr. 2022, 22, 3996–4007. [Google Scholar] [CrossRef]
  10. Wang, J.; Xiao, S.; Hayat, K.; Liao, X.; Chen, J.; Zhang, L.; Xie, Y. Investigating the Effects of Elevation on Microbial Communities and Soil Properties at Fanjing Mountain, China. Forests 2024, 15, 1980. [Google Scholar] [CrossRef]
  11. Shigyo, N.; Umeki, K.; Hirao, T. Plant functional diversity and soil properties control elevational diversity gradients of soil bacteria. FEMS Microbiol. Ecol. 2019, 95, fiz025. [Google Scholar] [CrossRef] [PubMed]
  12. Shen, C.; He, J.-Z.; Ge, Y. Seasonal dynamics of soil microbial diversity and functions along elevations across the treeline. Sci. Total Environ. 2021, 794, 148644. [Google Scholar] [CrossRef]
  13. Liu, J.-J.; Jin, L.; Shan, Y.-X.; Burgess, K.S.; Ge, X.-J. Elevation explains variation in soil microbial diversity and community composition under experimental warming and fertilization treatments in mountain meadows. Appl. Soil Ecol. 2022, 171, 104311. [Google Scholar] [CrossRef]
  14. Fu, F.; Li, J.; Li, S.; Chen, W.; Ding, H.; Xiao, S.; Li, Y. Elevational distribution patterns and drivers of soil microbial diversity in the Sygera Mountains, southeastern Tibet, China. Catena 2023, 221, 106738. [Google Scholar] [CrossRef]
  15. Zeng, Q.; Liu, D.; An, S. Decoupled diversity patterns in microbial geographic distributions on the arid area (the Loess Plateau). Catena 2021, 196, 104922. [Google Scholar] [CrossRef]
  16. Zeng, Q.; An, S.; Liu, Y.; Wang, H.; Wang, Y. Biogeography and the driving factors affecting forest soil bacteria in an arid area. Sci. Total Environ. 2019, 680, 124–131. [Google Scholar] [CrossRef]
  17. Fierer, N.; Jackson, R.B. The diversity and biogeography of soil bacterial communities. Proc. Natl. Acad. Sci. USA 2006, 103, 626–631. [Google Scholar] [CrossRef]
  18. Liu, L.; Zhu, K.; Krause, S.M.; Li, S.; Wang, X.; Zhang, Z.; Shen, M.; Yang, Q.; Lian, J.; Wang, X. Changes in assembly processes of soil microbial communities during secondary succession in two subtropical forests. Soil Biol. Biochem. 2021, 154, 108144. [Google Scholar] [CrossRef]
  19. Yu, C.; Han, F.; Fu, G. Effects of 7 years experimental warming on soil bacterial and fungal community structure in the Northern Tibet alpine meadow at three elevations. Sci. Total Environ. 2019, 655, 814–822. [Google Scholar] [CrossRef]
  20. Tang, Z.; Fang, J. Temperature variation along the northern and southern slopes of Mt. Taibai, China. Agric. For. Meteorol. 2006, 139, 200–207. [Google Scholar] [CrossRef]
  21. He, H.; Zhang, Q.; Zhou, J.; Fei, J.; Xie, X. Coupling climate change with hydrological dynamic in Qinling Mountains, China. Clim. Change 2009, 94, 409–427. [Google Scholar] [CrossRef]
  22. Zhou, L.; Zhou, Q.; Chen, Y.; Zeng, Q.; Li, J.; Hu, M.; Yu, B.; Chen, R. Altitude-induced shifts in bacterial communities involved in soil organic phosphorus cycling on Taibai mountain. Catena 2025, 255, 109014. [Google Scholar] [CrossRef]
  23. Bao, S.D. Soil Agrochemical Analysis, 3rd ed.; China Agriculture Press: Beijing, China, 2000. [Google Scholar]
  24. Olsen, S.R. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate; US Department of Agriculture: Washington, DC, USA, 1954. [Google Scholar]
  25. Wei, X.; Hu, Y.; Razavi, B.S.; Zhou, J.; Shen, J.; Nannipieri, P.; Wu, J.; Ge, T. Rare taxa of alkaline phosphomonoesterase-harboring microorganisms mediate soil phosphorus mineralization. Soil Biol. Biochem. 2019, 131, 62–70. [Google Scholar] [CrossRef]
  26. Zeng, Q.; An, S.; Liu, Y. Soil bacterial community response to vegetation succession after fencing in the grassland of China. Sci. Total Environ. 2017, 609, 2–10. [Google Scholar] [CrossRef] [PubMed]
  27. Bottomley, P.J.; Angle, J.S.; Weaver, R. Methods of Soil Analysis, Part 2: Microbiological and Biochemical Properties; John Wiley & Sons: Hoboken, NJ, USA, 2020; Volume 12. [Google Scholar]
  28. Walkley, A.; Black, I.A. An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci. 1934, 37, 29–38. [Google Scholar] [CrossRef]
  29. Zeng, Q.; An, S. Identifying the biogeographic patterns of rare and abundant bacterial communities using different primer sets on the loess plateau. Microorganisms 2021, 9, 139. [Google Scholar] [CrossRef]
  30. Caporaso, J.G.; Lauber, C.L.; Walters, W.A.; Berg-Lyons, D.; Lozupone, C.A.; Turnbaugh, P.J.; Fierer, N.; Knight, R. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. USA 2011, 108, 4516–4522. [Google Scholar] [CrossRef]
  31. Callahan, B.J.; McMurdie, P.J.; Rosen, M.J.; Han, A.W.; Johnson, A.J.A.; Holmes, S.P. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 2016, 13, 581–583. [Google Scholar] [CrossRef]
  32. Liu, C.; Cui, Y.; Li, X.; Yao, M. microeco: An R package for data mining in microbial community ecology. FEMS Microbiol. Ecol. 2020, 97, fiaa255. [Google Scholar] [CrossRef]
  33. Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 2003, 14, 927–930. [Google Scholar] [CrossRef]
  34. Bryant, J.A.; Lamanna, C.; Morlon, H.; Kerkhoff, A.J.; Enquist, B.J.; Green, J.L. Microbes on mountainsides: Contrasting elevational patterns of bacterial and plant diversity. Proc. Natl. Acad. Sci. USA 2008, 105, 11505–11511. [Google Scholar] [CrossRef] [PubMed]
  35. Badgley, C.; Fox, D.L. Ecological biogeography of North American mammals: Species density and ecological structure in relation to environmental gradients. J. Biogeogr. 2000, 27, 1437–1467. [Google Scholar] [CrossRef]
  36. Merino-Martín, L.; Hernández-Cáceres, D.; Reverchon, F.; Angeles-Alvarez, G.; Zhang, G.; Dunoyer de Segonzac, D.; Dezette, D.; Stokes, A. Habitat partitioning of soil microbial communities along an elevation gradient: From plant root to landscape scale. Oikos 2023, 2023, e09034. [Google Scholar] [CrossRef]
  37. Nottingham, A.T.; Bååth, E.; Reischke, S.; Salinas, N.; Meir, P. Adaptation of soil microbial growth to temperature: Using a tropical elevation gradient to predict future changes. Glob. Change Biol. 2019, 25, 827–838. [Google Scholar] [CrossRef]
  38. Shen, C.; Ni, Y.; Liang, W.; Wang, J.; Chu, H. Distinct soil bacterial communities along a small-scale elevational gradient in alpine tundra. Front. Microbiol. 2015, 6, 582. [Google Scholar] [CrossRef]
  39. Shen, C.; Gunina, A.; Luo, Y.; Wang, J.; He, J.Z.; Kuzyakov, Y.; Hemp, A.; Classen, A.T.; Ge, Y. Contrasting patterns and drivers of soil bacterial and fungal diversity across a mountain gradient. Env. Microbiol. 2020, 22, 3287–3301. [Google Scholar] [CrossRef] [PubMed]
  40. Nottingham, A.T.; Fierer, N.; Turner, B.L.; Whitaker, J.; Ostle, N.J.; McNamara, N.P.; Bardgett, R.D.; Leff, J.W.; Salinas, N.; Silman, M.R.; et al. Microbes follow Humboldt: Temperature drives plant and soil microbial diversity patterns from the Amazon to the Andes. Ecology 2018, 99, 2455–2466. [Google Scholar] [CrossRef]
  41. Donhauser, J.; Frey, B. Alpine soil microbial ecology in a changing world. FEMS Microbiol. Ecol. 2018, 94, fiy099. [Google Scholar] [CrossRef]
  42. Wang, C.; Ma, L.; Zuo, X.; Ye, X.; Wang, R.; Huang, Z.; Liu, G.; Cornelissen, J.H.C. Plant diversity has stronger linkage with soil fungal diversity than with bacterial diversity across grasslands of northern China. Glob. Ecol. Biogeogr. 2022, 31, 886–900. [Google Scholar] [CrossRef]
  43. Fierer, N.; Lauber, C.L.; Ramirez, K.S.; Zaneveld, J.; Bradford, M.A.; Knight, R. Comparative metagenomic, phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients. ISME J. 2012, 6, 1007–1017. [Google Scholar] [CrossRef]
  44. Wardle, D.A.; Bardgett, R.D.; Klironomos, J.N.; Setala, H.; Van Der Putten, W.H.; Wall, D.H. Ecological linkages between aboveground and belowground biota. Science 2004, 304, 1629–1633. [Google Scholar] [CrossRef]
  45. Ni, Y.; Yang, T.; Ma, Y.; Zhang, K.; Soltis, P.S.; Soltis, D.E.; Gilbert, J.A.; Zhao, Y.; Fu, C.; Chu, H. Soil pH determines bacterial distribution and assembly processes in natural mountain forests of eastern China. Glob. Ecol. Biogeogr. 2021, 30, 2164–2177. [Google Scholar] [CrossRef]
  46. Venkatachalam, S.; Kannan, V.M.; Saritha, V.N.; Loganathachetti, D.S.; Mohan, M.; Krishnan, K.P. Bacterial diversity and community structure along the glacier foreland of Midtre Lovénbreen, Svalbard, Arctic. Ecol. Indic. 2021, 126, 107704. [Google Scholar] [CrossRef]
  47. Tian, Q.; Jiang, Y.; Tang, Y.; Wu, Y.; Tang, Z.; Liu, F. Soil pH and organic carbon properties drive soil bacterial communities in surface and deep layers along an elevational gradient. Front. Microbiol. 2021, 12, 646124. [Google Scholar] [CrossRef] [PubMed]
  48. Cheng, J.; Zhao, M.; Cong, J.; Qi, Q.; Xiao, Y.; Cong, W.; Deng, Y.; Zhou, J.; Zhang, Y. Soil pH exerts stronger impacts than vegetation type and plant diversity on soil bacterial community composition in subtropical broad-leaved forests. Plant Soil 2020, 450, 273–286. [Google Scholar] [CrossRef]
  49. Griffiths, R.I.; Thomson, B.C.; James, P.; Bell, T.; Bailey, M.; Whiteley, A.S. The bacterial biogeography of British soils. Environ. Microbiol. 2011, 13, 1642–1654. [Google Scholar] [CrossRef]
  50. Ma, L.; Liu, L.; Lu, Y.; Chen, L.; Zhang, Z.; Zhang, H.; Wang, X.; Shu, L.; Yang, Q.; Song, Q. When microclimates meet soil microbes: Temperature controls soil microbial diversity along an elevational gradient in subtropical forests. Soil Biol. Biochem. 2022, 166, 108566. [Google Scholar] [CrossRef]
  51. Karimi, B.; Terrat, S.; Dequiedt, S.; Saby, N.P.; Horrigue, W.; Lelièvre, M.; Nowak, V.; Jolivet, C.; Arrouays, D.; Wincker, P. Biogeography of soil bacteria and archaea across France. Sci. Adv. 2018, 4, eaat1808. [Google Scholar] [CrossRef]
  52. Sait, M.; Davis, K.E.; Janssen, P.H. Effect of pH on isolation and distribution of members of subdivision 1 of the phylum Acidobacteria occurring in soil. Appl. Env. Microb. 2006, 72, 1852–1857. [Google Scholar] [CrossRef]
  53. Naether, A.; Foesel, B.U.; Naegele, V.; Wüst, P.K.; Weinert, J.; Bonkowski, M.; Alt, F.; Oelmann, Y.; Polle, A.; Lohaus, G. Environmental factors affect acidobacterial communities below the subgroup level in grassland and forest soils. Appl. Env. Microb. 2012, 78, 7398–7406. [Google Scholar] [CrossRef]
  54. Bárcenas-Moreno, G.; Gómez-Brandón, M.; Rousk, J.; Bååth, E. Adaptation of soil microbial communities to temperature: Comparison of fungi and bacteria in a laboratory experiment. Glob. Change Biol. 2009, 15, 2950–2957. [Google Scholar] [CrossRef]
  55. Zhang, Y.; Shen, H.; He, X.; Thomas, B.W.; Lupwayi, N.Z.; Hao, X.; Thomas, M.C.; Shi, X. Fertilization Shapes Bacterial Community Structure by Alteration of Soil pH. Front. Microbiol. 2017, 8, 1325. [Google Scholar] [CrossRef] [PubMed]
  56. Ren, B.; Hu, Y.; Chen, B.; Zhang, Y.; Thiele, J.; Shi, R.; Liu, M.; Bu, R. 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. 2018, 8, 5619. [Google Scholar] [CrossRef] [PubMed]
  57. Zeng, Q.; Mei, T.; Delgado-Baquerizo, M.; Wang, M.; Tan, W. Suppressed phosphorus-mineralizing bacteria after three decades of fertilization. Agric. Ecosyst. Environ. 2022, 323, 107679. [Google Scholar] [CrossRef]
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Figure 1. Locations of sampling points and soil sampling protocol.
Figure 1. Locations of sampling points and soil sampling protocol.
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Figure 2. Soil bacterial diversity characteristics across different elevations. A1: 2406 m; A2: 2809 m; A3: 3044 m; A4: 3204 m. Different letters indicate significant differences among elevations (p < 0.05).
Figure 2. Soil bacterial diversity characteristics across different elevations. A1: 2406 m; A2: 2809 m; A3: 3044 m; A4: 3204 m. Different letters indicate significant differences among elevations (p < 0.05).
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Figure 3. Soil bacterial community compositions at phylum and class levels across different elevations. A1: 2406 m; A2: 2809 m; A3: 3044 m; A4: 3204 m.
Figure 3. Soil bacterial community compositions at phylum and class levels across different elevations. A1: 2406 m; A2: 2809 m; A3: 3044 m; A4: 3204 m.
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Figure 4. Diversity indices of different microbial taxa across different elevations. A1: 2406 m; A2: 2809 m; A3: 3044 m; A4: 3204 m. Different letters indicate significant differences among elevations (p < 0.05).
Figure 4. Diversity indices of different microbial taxa across different elevations. A1: 2406 m; A2: 2809 m; A3: 3044 m; A4: 3204 m. Different letters indicate significant differences among elevations (p < 0.05).
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Figure 5. Structural characteristics of dominant bacterial communities across different elevations. A1: 2406 m; A2: 2809 m; A3: 3044 m; A4: 3204 m.
Figure 5. Structural characteristics of dominant bacterial communities across different elevations. A1: 2406 m; A2: 2809 m; A3: 3044 m; A4: 3204 m.
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Figure 6. RDA and random forest model analysis of the effects of environmental factors on overall soil bacterial community diversity and community structure. A1: 2406 m; A2: 2809 m; A3: 3044 m; A4: 3204 m. ** indicate significant effects, ns means no significant effects.
Figure 6. RDA and random forest model analysis of the effects of environmental factors on overall soil bacterial community diversity and community structure. A1: 2406 m; A2: 2809 m; A3: 3044 m; A4: 3204 m. ** indicate significant effects, ns means no significant effects.
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Figure 7. Regression analysis between the β-diversity (Bray–Curtis distance) and elevation change (Euclidean distance) in dominant bacterial communities.
Figure 7. Regression analysis between the β-diversity (Bray–Curtis distance) and elevation change (Euclidean distance) in dominant bacterial communities.
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Figure 8. Influence of environmental factors on dominant soil bacterial communities through the Mantel test.
Figure 8. Influence of environmental factors on dominant soil bacterial communities through the Mantel test.
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Figure 9. Variation partitioning analysis of the effects of mean annual temperature (MAT) and soil properties on bacterial community structure. Residuals represent unexplained variation. MAT was estimated using an empirical formula for the northern slope: MAT = −0.00495 × elevation + 17.1875.
Figure 9. Variation partitioning analysis of the effects of mean annual temperature (MAT) and soil properties on bacterial community structure. Residuals represent unexplained variation. MAT was estimated using an empirical formula for the northern slope: MAT = −0.00495 × elevation + 17.1875.
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Figure 10. Elevation-induced pattern of soil bacterial α-and β-diversity on Taibai Mountain. Different letters indicate significant differences among elevations (p < 0.05).
Figure 10. Elevation-induced pattern of soil bacterial α-and β-diversity on Taibai Mountain. Different letters indicate significant differences among elevations (p < 0.05).
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Table 1. Soil properties at different elevations on Taibai Mountain.
Table 1. Soil properties at different elevations on Taibai Mountain.
SiteElevation/mMAT/°CPlant DiversityNO3−N/mg·kg−1NH4+N/mg·kg−1pHAVP/mg·kg−1SOM/g·kg−1
A432041.330.0111.41 ± 2.09 b9.17 ± 1.85 b5.01 ± 0.11 a14.62 ± 7.34 a124.92 ± 42.15 a
A330442.120.839.29 ± 4.07 b13.57 ± 3.09 a5.01 ± 0.2 a5.53 ± 1.74 b65.59 ± 19.18 ab
A228093.281.1516.44 ± 3.25 a7.2 ± 0.54 b4.74 ± 0.44 a13.27 ± 5.82 a59.2 ± 23.1 b
A124065.281.2912.51 ± 2.82 b12.56 ± 1.36 a4.88 ± 0.25 a8.29 ± 3.79 ab95.88 ± 44.01 a
Note: MAT, mean annual temperature; NO3−N, soil nitrate nitrogen; NH4+N, soil ammonium nitrogen; AVP, soil available phosphorus; SOM, soil organic matter. Different letters indicate significant differences among elevations (p < 0.05).
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Li, Z.; Wei, X.; Qi, Y. Elevational Patterns and Environmental Drivers of Dominant Bacterial Communities in Alpine Forest Soils of Mt. Taibai, China. Forests 2025, 16, 814. https://doi.org/10.3390/f16050814

AMA Style

Li Z, Wei X, Qi Y. Elevational Patterns and Environmental Drivers of Dominant Bacterial Communities in Alpine Forest Soils of Mt. Taibai, China. Forests. 2025; 16(5):814. https://doi.org/10.3390/f16050814

Chicago/Turabian Style

Li, Zhigang, Xin Wei, and Yanbing Qi. 2025. "Elevational Patterns and Environmental Drivers of Dominant Bacterial Communities in Alpine Forest Soils of Mt. Taibai, China" Forests 16, no. 5: 814. https://doi.org/10.3390/f16050814

APA Style

Li, Z., Wei, X., & Qi, Y. (2025). Elevational Patterns and Environmental Drivers of Dominant Bacterial Communities in Alpine Forest Soils of Mt. Taibai, China. Forests, 16(5), 814. https://doi.org/10.3390/f16050814

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