Land use types and elevation gradients jointly influence soil bacterial community diversity and functions in the Gaoligong Mountains

Abstract

Land use types and elevation gradients are key determinants of soil environment, thereby shaping the composition and diversity of soil bacterial communities. Nevertheless, our understanding of how the composition, diversity, and functions of soil bacterial communities vary among land use types along elevation gradients remains limited. The present study was conducted in the biodiversity-rich Gaoligong Mountains, where soil samples were collected from shrublands (SL), coffee fields (CF), maize fields (MF), and orange fields (OF) along an elevation gradient spanning 900–1800 m (i.e., 900–1200 m, 1200–1500 m, and 1500–1800 m). A 16 S rRNA amplicon sequencing was applied to assess the composition of soil bacterial community. In addition, we employed FAPROTAX to perform functional classification based on the 16 S sequencing data. The results showed that land use types, elevation, and their interactions had significant affected on soil chemical properties, α diversity and functions of soil bacterial communities. PERMANOVA analysis further revealed that both land use types (R² = 0.21) and elevation (R² = 0.09) both had significant effects on the bacterial β diversity. The nine measured soil chemical properties explained 86.35%, 86.88%, and 83.75% of the variation in soil bacterial community composition at low, medium, and high elevation, respectively, suggesting that soil chemical conditions were major determinants of bacterial community composition across elevation gradients. Among these factors, soil nitrogen variables including NO₃^--N, TN, NO₄^་-N played particularly role in shaping soil bacterial community composition. Overall, land use types and elevation gradients jointly shape the composition, diversity, and function of soil bacterial communities in the Gaoligong Mountains. This study can help enhance our understanding of how anthropogenic and natural factors interact to influence soil microbial communities in mountain ecosystems, and provides a scientific basis for soil health management and the conservation of microbial ecosystem functions under global environmental change.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12866-026-05371-3.

Introduction

The Gaoligong Mountains, located in western Yunnan along the China-Myanmar border, extend for more than 600 km from the southeastern margin of the Qinghai-Tibet Plateau to the northern reaches of the Indo-China Peninsula, the mountain range spans approximately five degrees of latitude and encompasses remarkable environmental heterogeneity [1]. Situated at the intersection of three global biodiversity hotspots, namely, the Mountains of Southwest China, the Eastern Himalayas, and the Indo-Burma region, the Gaoligong Mountains harbor exceptionally rich biodiversity, and are widely recognized as one of China’s most important centers of species diversity and endemism [2–5]. Despite covering only 0.36% of China’s total land area, the Gaoligong Mountains support an extraordinarily high proportion of China’s biodiversity, including approximately half of China’s bird species, 30% of mammal species, 11% of reptile species, and 17% of higher plant species [6, 7]. Reflecting their outstanding biodiversity and evolutionary importance, the Gaoligong Mountains have been recognized as the ‘cradle of mammalian ancestors’, the ‘cradle of east Asian flora’, and one of the world’s most important reservoirs of genetic diversity. Soil bacteria play a vital ecological role in carbon and nitrogen cycling, including the decomposition of organic matter, carbon and nitrogen fixation and sequestration, and nitrification and denitrification, thereby directly or indirectly affecting the health of soil, plants, and humans [8, 9]. Recently, research has increasingly focused on the carbon (C) and nitrogen (N) functional cycling groups within soil bacterial community [10–12]. Although extensive surveys have documented the diversity of birds, insects, and higher plants in the Gaoligong Mountains, studies investigating the diversity and functions of soil bacterial community in this biodiversity hotspot remain limited.

Land-use practices are among the major anthropogenic factors influencing soil biogeochemical properties and the composition of soil bacterial community. Numerous studies have shown that natural ecosystems (e.g., forests, shrublands, and grasslands) and agricultural lands differ significantly in their soil environmental characteristics, leading to substantial variations in the diversity and composition of soil bacterial communities [13–15]. Traditional agricultural practices, such as the use of chemical fertilizers and monoculture cropping, can alter the chemical properties of soils in pre-existing ecosystems, which in turn affects the composition and relative abundance of soil bacterial community [16–19]. Agricultural management practices, particularly the application of inorganic and organic fertilizers, have been shown to exert significant effects on the composition and diversity of soil bacterial community [20, 21]. Futhermore, elevation is another important factor shaping soil bacterial community. For example, a global meta-analysis has shown that soil bacterial diversity decreased significantly with increasing elevation [22]. However, other studies have reported no significant changes in soil bacterial diversity along elevation gradients [23]. Regardless of whether soil properties decrease or increase directly with elevation, elevation-induced changes in key soil properties, such as pH, soil organic carbon, and total nitrogen, can indirectly affect the composition and diversity of soil bacterial community [23]. Although agricultural land-use practices and elevation gradients represent anthropogenic and natural drivers, respectively,, both of which can indirectly affect soil bacterial communities through their effects on soil physicochemical properties [24, 25]. Although natural environmental factors exert significant influence over soil bacterial communities, their effects are generally less pronounced than those of agricultural land-use practices [26]. Nevertheless, studies examining the interactive effects between land use practices and elevation affects soil bacterial community structure and diversity remain limited.

The diverse topographic features and climatic conditions of the Gaoligong Mountains sustain rich biodiversity, including a wide variety of tree, bird and mammal species, making the region an ideal natural laboratory for exploring biodiversity patterns across both aboveground and belowground communities. Given that biodiversity research in the Gaoligong Mountains has predominantly focused on aboveground communities, our study aims to address this knowledge gap by investigating the composition and diversity of soil bacterial community in alpine shrublands. Alpine shrublands are a type of vegetation dominated by cold-tolerant mesophytic or xerophytic shrubs [27, 28]. They play an irreplaceable role in community succession, ecosystem carbon sequestration, and biodiversity conservation, and are one of the primary vegetation types in the Gaoligong Mountains [29]. However, as the population continues to grow, an increasing area of alpine shrublands has been converted to agricultural use. Since the late 1990s, farmers in the Gaoligong Mountains have gradually shifted from growing traditional food crops (e.g., maize and rice) to cash crops (e.g., sugarcane, coffee and oranges) to increase their income. Today, the shrublands in the Gaoligong Mountains exhibit a patchy distribution pattern, with extensive areas of maize, orange and coffee fields, resulting in a diverse range of land uses. Furthermore, in this high-altitude ecosystem, elevation is a key environmental factor influencing soil bacteria. However, how elevation, land use type, and their interactions affect the composition, diversity, and ecological functions of soil bacterial communities in the Gaoligong Mountains remains inadequately understood. We selected Baihualing Village at the southern foot of the Gaoligong Mountains as our study site. Using high-throughput sequencing technology, we examined the composition, diversity, and ecological functions of soil bacterial communities in shrublands and agricultural lands across elevation gradients, and identified key environmental factors driving these patterns. We hypothesized that land use types, elevation, and their interaction significantly influence the diversity and ecological functions of soil bacterial communities. Specifically, we addressed the following questions: (1) How do land use types, elevation, and their interactions affect soil chemical properties? (2) Which soil chemical properties serve as key drivers of shifts in soil bacterial community composition and diversity? (3) How do land use types, elevation, and their interactions affect soil bacterial C and N cycling functional groups, and what environmental factors regulate these responses?

Materials and methods

Study area and sampling

The Gaoligong Mountains (23°50’-28°30’N, 97°31’-99°05’E) are located in the northwestern border area between China and Myanmar, encompassing the Nujiang Lisu Autonomous Prefecture and the western part of Baoshan City in Yunnan Province (Fig. 1). Baihualing Village, situated on the southern slope of the Gaoligong Mountains, spans an area of 18.6 square kilometers, with elevations ranging from 800 m to 1860 m. This area experiences a subtropical and warm temperate monsoon climate, with an average annual temperature of 21.3 ℃ and an average annual rainfall of 1225 mm, making it suitable for a variety of economic crops. Baihualing Village mainly cultivates cash crops such as maize, coffee, oranges and walnuts. In particular, large areas of maize, coffee and orange fields are present, making the soils beneath these three types of agricultural land uses the focus of the present study. The selected maize, coffee, and orange fields were all planted in the late 1990s, and each plot has been planted with the same crop for 25 to 26 years. In addition, the maize and coffee fields were managed using tilled agriculture and fertilized with compound fertilizers, while the orange fields were managed using no-till agriculture with organic fertilizer, with three types of fields being fertilized 1–2 times per year.

Fig. 1.

Distribution of study areas (a-b) and sampling sites (c). SL: shrublands; CF: coffee fields; MF: maize fields; OF: orange fields

Soil sampling was conducted in January 2024 within the study area. The altitude range for sampling was 900–1800 m, divided into low (900–1200 m), medium (1200–1500 m), and high (1500–1800 m) elevations. Three elevation gradients were selected, each including maize fields (MF), coffee fields (CF), and orange fields (OF), with adjacent shrublands (SL) chosen as a control. Thus, each elevation gradient included four land use types. The species composition of the shrublands is similar across different elevations, and the vegetation is primarily composed of plants such as Heteropogon contortus, Eulaliopsis binata, Bothriochloa pertusa, Aristida adscensionis, Campylotropis delavayi, Broussonetia papyrifera, and Vachellia farnesiana. One land use type at the same elevation is treated as a sampling point, with a minimum distance of 100 m between each sampling point. At each sampling point, three 3 m × 3 m small plots were randomly established. Within each small plot, five points were randomly selected along an “S” shaped curve to collect surface soil samples (0–10 cm). Soil samples from the same small plot were thoroughly mixed to form a composite sample. 3 composite soil samples were collected for each land use type at the same elevation, resulting in a total of 36 composite soil samples (3 elevations × 4 land use types × 3 replicates). The soil samples were divided into two parts using the tetrad method–one portion was used for the analysis of soil bacterial communities, and then stored in a refrigerator at -80℃. The other portion was used for the analysis of soil chemical properties, and then stored in a refrigerator at 4℃.

Determination of soil chemical properties

Soil samples were dried and passed through a 2 mm sieve mesh for the determination of each soil chemical property index. Among them, soil pH was determined using a pH meter (pHS-3E) in soil-to-water solution with a ratio of 1:25 (g/v). Soil total carbon (TC) was determined by combustion-infrared absorption spectrometry using a high-frequency infrared carbon and sulphur meter (HCS878A、ACJ10). Soil total nitrogen (TN) was determined using a fully automated Kjeldahl nitrogen tester (K9840). Soil total phosphorus (TP), nitrate nitrogen (NO₃⁻-N) and ammonium nitrogen (NH₄⁺-N) were determined using a UV-visible spectrophotometer (TU-1900), soil organic carbon (SOC) and dissolved organic carbon (DOC) were determined using the potassium dichromate external heating method, with an electronic analysing balance (XB220A). All of the above methods were performed in accordance with Soil Agrochemical Analysis (3rd Edition) [30]. Finally, the organic carbon to nitrogen ratio was obtained from the ratio of soil organic carbon to total nitrogen (C: N) [31].

DNA extraction and high-throughput sequencing

Total genomic DNA was extracted from 0.5 g of fresh soil sieved through a 2-mm mesh using the soil kit (MP Biomedicals, Santa Ana, CA). Genomic DNA integrity was examined by agarose gel electrophoresis, and total genomic DNA concentration and purity were examined by Nanodrop 2000 and Qubit 3.0 spectrophotometers. The 16 S rRNA gene of the V4-V5 highly variable region was amplified with primers 515 F (5’-GTGCGCMGCCGGG-3’) and 907R (5’-CCGTCAATTCMTTTRAGTTT-3’). PCR was performed under the following conditions: denaturation at 94◦C for 5 min, followed by 30 cycles (94◦C for 30 s, 52◦C for 30 s, and 72◦C for 45 s), and then extended at 72◦C for 10 min. The amplification products were verified by 1.0% agarose gel electrophoresis. Finally, sequencing was performed using an Illumina NovaSeq 6000 sequencer. Raw read sequences were processed in QIME247, using the default parameters to eliminate sequences of poor quality (quality score < 25, homopolymer runs of > 6 nt and length > 200 nt) [31]. Adapter and primer sequences were trimmed using the cutadapt plugin. The DADA2 plugin was used for quality control and identification of amplicon sequence variants (ASVs) [32]. Classification assignment of bacterial ASVs representative sequences was performed by a pre-trained Naive Bayes classifier trained on SILVA (version 138.1) with a confidence threshold of 0.8.

Statistical analysis

All data were pre-processed using Excel and IBM SPSS Statistics 27 software. Based on the number of the ASV, α diversity (including Observed, Shannon and AEC indices) were calculated using the “mothur” package, and principal coordinate analysis (PCoA) was performed using Bray-Curtis distances to investigate differences in bacterial communities β diversity. Prior to analysis, all datasets were subjected to normality and homogeneity of variance tests to ensure data integrity. A two-way analysis of variance was used to analyze the interaction between land use type and elevation on soil chemical properties and soil bacterial α diversity. Additionally, one-way analysis of variance were conducted separately for land use type and elevations, and Tukey’s HSD (Honest Significant Differences) test was used for multiple comparisons. Permutation Multivariate Analysis of Variance (PERMANOVA, 999 permutations) was used to quantitatively analyze the effects of land use type and elevation on soil bacterial community composition. Redundancy analysis (RDA) was generated using “Vegan” package to analyse the correlation between soil bacterial community composition and environmental factors, Pearson correlation analysis was performed to study the correlation between dominant bacterial phyla, α diversity, abundances of functional groups, and environmental factors. These data were analyzed using R software. Based on 16 S rRNA amplicon sequencing data, the soil bacterial community was functionally annotated using FAPROTAX, a tool capable of identifying the abundance of soil bacteria involved in carbon (C) and nitrogen (N) cycling genes, with taxonomic criteria referenced from the studies by Huang and Fan [13, 33]. These genes were grouped into C and N cycling functional groups, respectively. Figures were prepared using Origin 2024 and R software (version 4.3.2).

Results

Soil chemical properties

The results of the two-way ANOVA showed that land use types, elevation gradients, and their interactions significantly affected soil chemical properties (P < 0.05; Fig. 2). Significant differences in soil chemical properties were observed among land use types. At low elevations, SL soils exhibited the highest pH. Compared with SL, the pH of the three agricultural land types decreased significantly by 7.0-28.8%, and soil NO₃^--N decreased significantly by 20.0-43.9%. In contrast, soil TC, TN, TP, and SOC in CF increased by 124.7%, 147.9%, 120.6%, and 156.4%, respectively, whereas the corresponding increases in MF were 36.5%, 38.0%, 52.9%, and 31.5%. However, soil TC, TN, TP, and SOC contents in OF were significantly lower than those in SL, decreasing by 65.9%, 49.3%, 44.1%, and 67.7%, respectively. At medium elevations, the three agricultural land-use types exhibited significantly higher soil pH, TC, TN, TP, NO₃^།-N, SOC, and DOC than SL. Compared with SL, soil pH increased by 7.7–53.4%, TC by 74.3-199.1%, TN by 244.0-382.0%, TP by 48.2-109.3%, NO₃^།-N by 17.8–26.6%, SOC by 85.6-226.5%, and DOC by 10.0–60.0%. In contrast, the soil C: N ratio decreased significantly by 69.6–74.4%. At high elevations, compared with the SL, the three agricultural land-use types exhibited significantly higher soil pH, with increases ranging from 5.5% to 14.4%. In contrast, TN, NO₃^།-N, SOC, and DOC were significantly lower, decreasing by 35.1–72.2%, 20.8–41.3%, 20.8–41.3%, and 5.8–57.7%, respectively.

Fig. 2.

Effects of different land use types and elevation on soil chemical properties. a pH; b TC; c TN; d TP; e NO₄⁺-N; f NO₃^－-N; g SOC; h DOC; i C:N. Lowercase letters indicate significant differences in alpha diversity of bacterial community between different land uses (P < 0.05); uppercase letters indicate significant differences between different elevations (P < 0.05). SL: shrublands; CF: coffee fields; MF: maize fields; OF: orange fields. TC, total carbon; TN, total nitrogen; TP, total phosphorus; NH₄⁺-N, ammonium nitrogen; NO₃^--N, nitrate nitrogen; SOC, soil organic carbon; DOC, dissolved organic carbon; C:N, C:N ratios

Elevation also had a significant effect on soil chemical properties (Fig. 2). For SL, soil TC, TP, NO₃^--N, SOC, and DOC concentrations showed increased with increasing elevation. For CF, soil pH, TC, TN, NO₃^།-N, SOC, and C: N exhibited a unimodal pattern along the elevation gradient, decreasing initially and then increasing, whereas soil TP and N₄⁺-N showed the opposite trend. For MF, soil pH followed a similar unimodal pattern, while soil TC, TN, TP, N₄⁺-N, and SOC displayed an inverse trend, increasing initially and then decreasing with elevation. For OF, soil pH, TC, TN, TP, NO₃^།-N, SOC, DOC, and C: N all increased progressively with increasing elevation, whereas NH₄⁺-N decreased.

α diversity of soil bacterial community

The results of two-way ANOVA showed that land use types, elevation, and their interaction significantly influenced diversity indices of soil bacterial communities (P < 0.05; Fig. 2). Regarding land use types, at low elevation, compared with SL, the Observed, Shannon, and ACE indices for CF were significantly higher by 11.6%, 2.5%, and 11.5%, respectively; there are no significant differences in the Observed and ACE indices between CF and MF, but there were significant differences in their Shannon indices. At medium elevation, compared with SL, the Observed indices for CF, MF, and OF were significantly higher by 35.0–51.7%, the ACE index was significantly higher by 35.3–52.2%, and the Shannon indices for CF and OF were significantly higher by 4.7–7%. At high elevation, compared with SL, the Observed, Shannon, and ACE indices for CF decreased significantly by 20.6%, 5.0%, and 20.7%, respectively, with he exception of the Shannon index for MF, no significant differences observed for MF and OF. These results indicate that the effects of land use type on soil bacterial α diversity varied across the elevation gradient.

Changes in elevation also led to significant changes in diversity indices of soil bacterial communities (P < 0.05; Fig. 2). For SL, the Observed, Shannon, and ACE indices showed a trend of first decreasing and then increasing with rising elevation, reaching their highest values at high elevation. For CF, the Observed, Shannon, and ACE indices showed a trend of decreasing with rising elevation. For MF, the Observed, and ACE indices showed a decreasing trend with increasing elevation. For OF, the Observed, Shannon, and ACE indices exhibited a pattern of first increasing and then decreasing with elevation at medium elevation; however, a significant difference in the Shannon index was observed only between low and medium elevations.

β diversity of soil bacterial community

PCoA analysis based on Bray-Curtis distance was conducted to examine the structure of soil bacterial communities across different land use types at various elevations (Fig. 3a). With regard to land use, except for CF, MF, and OF at high elevation, which were similar to one another and distinct from SL, all other land use types exhibited significant separation patterns. SL, CF, and MF all showed a trend of separation in soil bacterial community composition across different elevations, whereas the soil bacterial community composition of OF at medium and high elevation were similar to on another and different from those at low elevation. According to the PERMANOVA results, there were significant differences in soil bacterial community composition among different land use types and elevations (Fig. 4b, P < 0.01), but the effect of land use types (R² = 0.21) on soil bacterial community composition was stronger than that of elevation (R² = 0.09).

Fig. 3.

Effects of the land use types and elevation on soil bacterial community diversity indices. a Observed; b Shannon; c ACE. Lowercase letters indicate significant differences in alpha diversity of bacterial community between different land uses (P < 0.05); uppercase letters indicate significant differences between different elevations (P < 0.05). SL: shrublands; CF: coffee fields; MF: maize fields; OF: orange fields

Fig. 4.

Effects of land use types and elevation on soil bacterial community composition. a PCoA analysis based on the Bray-Curtis distance; b Relative abundances of soil bacterial communities at the phylum level. SL: shrublands; CF: coffee fields; MF: maize fields; OF: orange fields. * p<0.05, ** p<0.01, ***p<0.001

In total, 46 phyla and 530 families of bacteria were identified in 36 samples. The results indicate that the dominant bacterial phyla in soils across different land use types at various elevations are similar, although their relative abundances vary (Fig. 3b). The dominant phyla in all land use types included Acidobacteriota, Proteobacteria, Chloroflexi, Actinobacteriota, Planctomycetota, Bacteroidota, Gemmatimonadota, Myxococcota (relative abundance > 1%), and these dominant phyla accounted for 81.50–91.91% of all phyla, accounting for the vast majority of all phyla. At low elevation, compared with CF, MF, and OF, the relative abundances of Acidobacteriota and Proteobacteria were lower in SL, while the relative abundance of Chloroflexi was higher. At medium elevation, compared with CF, MF, and OF, the relative abundances of Acidobacteriota and Chloroflexi in SL increased, while that of Proteobacteria decreased. At high elevation, compared with CF, MF, and OF, the relative abundance of Proteobacteria in SL increased, while that of Chloroflexi decreased; the relative abundance of Acidobacteriota in SL was lower than that in CF and OF but higher than that in MF. The relative abundance of Acidobacteriota in SL, CF, and MF all followed a trend of first increasing and then decreasing with increasing elevation, whereas the trend in OF was the opposite; the relative abundance of Proteobacteria in SL first increased and then decreased with increasing altitude, while CF and MF showed the opposite trend, and OF showed a decreasing trend; the relative abundance of Chloroflexi in SL and OF first increased and then decreased with increasing elevation, while MF showed the opposite trend, and CF showed an increasing trend. Consequently, there are differences across land use types in the trends of relative abundance of the three dominant phyla (Acidobacteriota, Proteobacteria, Chloroflexi) as a function of elevation.

The dominant families vary across different elevations, and their relative abundances also differ (Figure S1). At low elevation, the dominant families were Pyrinomonadaceae, Gemmatimonadaceae, Chitinophagaceae, Nitrosomonadaceae, and Vicinamibacteraceae. Compared to CF, MF, and OF, the relative abundance of Pyrinomonadaceae was higher in SL, while that of Gemmatimonadaceae and Nitrosomonadaceae were both lower; At medium elevation, the dominant families shifted to Ktedonobacteraceae, Subgroup_2_family, Gemmatimonadaceae, Chitinophagaceae, and Nitrosomonadaceae. Compared to CF, MF, and OF, the relative abundances of Ktedonobacteraceae and Subgroup_2_family in SL increased, while those of Gemmatimonadaceae, Chitinophagaceae, and Nitrosomonadaceae all decreased; at high elevation, the dominant families were Vicinamibacteraceae, Pyrinomonadaceae, Chitinophagaceae, Gemmatimonadaceae, and Nitrosomonadaceae. Compared to CF, MF, and OF, the relative abundances of Vicinamibacteraceae, Chitinophagaceae, and Gemmatimonadaceae were all lower in SL.

Correlation between soil bacterial community and environmental factors

Correlation between soil bacterial community α diversity with environmental factors

At low elevation, the Shannon index showed a significant positive correlation with TC, TN, and SOC. At medium elevation, the Observed, Shannon, and ACE indices all showed significant positive correlations with pH, TC, TN, SOC, and DOC; the Observed and ACE indices showed significant positive correlations with TP and NO₃^--N, and significant negative correlations with C: N. At high elevations, the Observed, Shannon, and ACE indices showed significant positive correlations with TC, TN, TP, NH₄⁺-N, SOC, and DOC (P < 0.05). In summary, TC, TN, and SOC are all key environmental factors influencing soil bacterial community diversity indices, particularly at medium and high elevations.

Correlation between β diversity of soil bacterial community and environmental factors

The RDA analysis results indicate that the nine soil chemical properties accounted for 86.35%, 86.88%, and 83.75% of the total variance in soil bacterial community composition at low, medium, and high elevations, respectively, and were all able to adequately explain the variations in soil bacterial communities. At low elevation, soil NO₃^--N was the primary environmental factor influencing changes in soil bacterial community. At medium elevation, soil NO₃^།-N and TP were the primary environmental factors influencing changes in soil bacterial community. At high elevation, NH₄⁺-N and TN were the primary environmental factors influencing changes in soil bacterial community. Correlation analysis showed that at low elevations, soil NO₃^།-N was significantly positively correlated with Acidobacteriota and Gemmatimonadota, and significantly negatively correlated with Chloroflexi and Actinobacteriota; at medium elevation, soil TP was significantly positively correlated with Proteobacteria, Bacteroidota, and Myxococcota, and significantly negatively correlated with Chloroflexi; soil NO₃^།-N was significantly positively correlated with Proteobacteria and Bacteroidota, and significantly negatively correlated with Acidobacteriota and Chloroflexi; At high elevation, soil NH₄⁺-N was significantly positively correlated with Proteobacteria and Actinobacteriota, and significantly negatively correlated with Chloroflexi and Gemmatimonadota; soil TN was significantly positively correlated with Actinobacteriota, and significantly negatively correlated with Chloroflexi, Bacteroidota, and Gemmatimonadota.

C and N cycling functional groups of soil bacterial community

Functional predictions were performed on all samples using the FAPROTAX tool, identifying a total of 34 functional genes associated with soil C and N cycling. At low elevation, a total of 18 C cycling functional genes and 14 N cycling functional genes were detected; at medium elevation, a total of 18 C cycling functional genes and 14 N cycling functional genes were detected; at high elevation, a total of 19 C cycling functional genes and 16 N cycling functional genes were detected (Figure S2). The results of two-way ANOVA showed that land use types, elevation, and their interaction significantly influenced the abundance of soil bacterial functional genes (P < 0.05; Fig. 6). Regarding land use types, at low elevation, compared with SL, the abundance of C cycling related functional genes in CF, MF, and OF decreased significantly by 32.6–43.4%, and the abundance of N cycling related functional genes decreased by 38.8–57.0%; at medium elevation, compared with SL, the abundance of C and N cycling related functional genes in OF increased by 28.7% and 35.7%, respectively, with no significant differences observed in CF and MF; at high elevation, compared with SL, the abundance of C cycling related functional genes in CF, MF, and OF decreased significantly by 17.0–42.5%, while the abundance of N cycling related functional genes decreased by 38.9–52.6%.

Fig. 6.

Effects of the land use types and elevation on soil bacterial functional groups. a C cycling functional groups; b N cycling functional groups. Lowercase letters indicate significant differences in alpha diversity of bacterial communities between different land uses (P < 0.05); uppercase letters indicate significant differences between different elevations (P < 0.05). SL: shrublands; CF: coffee fields; MF: maize fields; OF: orange fields

Changes in elevation also result in significant changes in the abundance of soil bacterial functional genes (Fig. 6). For SL, the abundances of both C and N cycling related functional genes showed a trend of first decreasing and then increasing with increasing elevation, reaching their highest levels at high elevation; for CF, the abundance of carbon cycling related functional genes increased initially and then decreased with increasing elevation, while the trend for nitrogen cycling related functional genes was the opposite; for MF and OF, the abundances of both C and N cycling functional genes increased with increasing elevation, although no significant differences were observed among the three elevation levels for MF.

At low elevation, the abundance of C cycling functional groups was significantly positively correlated with soil pH, while the abundances of both C and N cycling functional groups were significantly negatively correlated with NO₃^--N; at medium elevation, the abundances of both C and N cycling functional groups were significantly positively correlated with pH, TC, SOC, and DOC; At high elevation, the abundances of both C and N cycling functional groups were significantly positively correlated with soil TC, TN, NH₄⁺-N, NO₃^།-N, SOC, and DOC, and significantly negatively correlated with soil pH; the relative abundance of the C cycling functional group was also significantly positively correlated with TP.

Discussion

Effects of land use types, elevation, and their interactions on the α diversity of soil bacterial communities

Two-way ANOVA analysis showed that land use types, elevation, and their interactions significantly affected the Observed, Shannon, and ACE indices of soil bacterial community, which is consistent with previous studies [34]. A global meta-analysis reported a general decline in bacterial diversity with increasing elevation [22]. In contrast, our results showed that the relationship between bacterial diversity and elevation vary among land use types. This suggests that the combined effects of anthropogenic disturbances and natural gradients may generate to nonlinear patterns in soil bacterial diversity. Regarding the effects of land use types, significant differences in soil bacterial diversity exist across different land use types, as demonstrated in numerous studies, and bacterial diversity in natural vegetation soils is significantly lower than that in agricultural soils [13, 14, 35, 36], which is consistent with our findings in low and medium elevation regions. Specifically, at low elevation, compared to SL, CF significantly increased bacterial diversity, which may be related to substantial improvements in soil TC, TN, and SOC (Fig. 2), as soil nutrients are key factors influencing soil bacteria [37, 38]. At medium elevation, both CF and OF exhibited significantly greater bacterial diversity than SL. Analysis of soil chemical properties at this elevation showed that soil pH, TC, TN, TP, SOC, and DOC were significantly higher in all three agricultural land use types than in SL. Furthermore, bacterial diversity indices were significantly positively correlated with soil pH, TC, TN, SOC, and DOC (P < 0.05; Table 1), further demonstrating that land use practices can create more favorable soil conditions than natural vegetation by enhancing nutrient availability and regulating soil pH [39, 40], thereby promoting soil bacterial diversity. Notably, in contrast to the patterns observed at low and medium elevations, agricultural land use at high elevations significantly reduced soil bacterial diversity compared with shrublands (Fig. 3). This decline may be associated with the relatively high soil pH (7.63–8.07) observed in agricultural soils at high elevations, as previous studies have shown that fertilization in alkaline soils can negatively affect soil bacterial diversity [41]. Furthermore, the effects of elevation on soil bacterial α diversity varied among land-use types, suggesting that the response of bacterial communities to elevation is strongly influenced by land-use practices. In SL, Shannon and ACE indices exhibited a unimodal pattern along the elevation gradient. Similar patterns have been reported in alpine shrublands [42]. In contrast, the α diversity indices in traditional CF and MF decreased monotonically with increasing elevation. This pattern suggests that traditional agricultural management may exacerbate the environmental constraints associated with higher elevation, such as lower temperatures and shorter growing seasons, thereby contributing to the loss of bacterial diversity at higher elevation. Unlike conventional agricultural practices, organic management can improve soil nutrient status [43, 44], potentially mitigating the negative effects of increasing elevation on soil bacterial diversity. Consistent with this expectation, no significant differences in bacterial α diversity were observed among elevations in OF, except for a significant difference in the Shannon index between low and medium elevations.

Table 1.

Correlation of bacterial community α diversity with chemical properties

Elevation	Index	pH	TC (g/kg)	TN (g/kg)	TP (g/kg)	NO4+-N (mg/kg)	NO3--N (mg/kg)	SOC (g/kg)	DOC (g/kg)	C: N
Low elevation	Observed	-0.29	0.43	0.51	0.45	0.14	0.45	0.46	0.54	0.42
	Shannon	0.02	0.59*	0.66*	0.56	0.10	0.13	0.66*	0.48	0.28
	ACE	-0.27	0.43	0.51	0.45	0.14	0.45	0.48	0.27	-0.01
Medium elevation	Observed	0.75**	0.91**	0.95**	0.62*	-0.15	0.92**	0.92**	0.79**	-0.70*
	Shannon	0.84**	0.84**	0.75**	0.29	0.17	0.47	0.82**	0.86**	-0.44
	ACE	0.75**	0.91**	0.95**	0.62*	-0.15	0.92**	0.92**	0.79**	-0.70*
High elevation	Observed	-0.47	0.71**	0.76**	0.68*	0.64*	0.56	0.78**	0.78**	0.19
	Shannon	-0.36	0.71**	0.74**	0.75**	0.64*	0.47	0.77**	0.81**	0.31
	ACE	-0.47	0.72**	0.76**	0.68*	0.64*	0.56	0.78**	0.78**	0.19

TC Total carbon, TN Total nitrogen, TP Total phosphorus, NH₄⁺-N Ammonium nitrogen, NO₃^--N Nitrate nitrogen, SOC Soil organic carbon, DOC Dissolved organic carbon, C:N, C:N ratios. * p<0.05, ** p<0.01

Effects of land use types and elevation on the β diversity of soil bacterial communities

The Bray-Curtis distance-based PCoA and PERMANOVA analysis consistently suggest that both land use types and elevation gradients significantly influence the β diversity of soil bacterial communities (Fig. 4b). Moreover, PERMANOVA revealed that land use types explained a greater proportion of the variation in bacterial community composition. This finding is consistent with previous studies [26], further supporting the view that, relative to the natural environmental gradient represented by elevation, anthropogenic disturbance exerts a more direct and intense shaping effect on soil bacterial community composition. The relative abundances of Acidobacteriota, Proteobacteria, and Chloroflexi varied significantly among different elevation gradients and land use types (Fig. 4a). Acidobacteriota are typical oligotrophic bacteria capable of utilizing nutrient-poor and recalcitrant carbon substrates [45]. At medium elevation, their abundance was significantly negatively correlated with soil pH. Since acidic conditions favor the growth of Acidobacteriota, their highest abundance was observed in the SL soils at medium elevation. Proteobacteria are among the most abundant and widely distributed bacterial phyla in soils [46]. Previous studies have shown that they play important roles in suppressing soil-borne diseases, promoting plant growth, fixing atmospheric nitrogen, and enhancing soil fertility [47–49]. Consequently, a higher abundance of Proteobacteria may contribute to accelerated nutrient cycling and improved soil ecosystem functioning. Our study found that the relative abundance of Proteobacteria in SL was lower than that in the three agricultural land-use types at both low and medium elevations. A plausible explanation is that agricultural management practices, particularly fertilization application, increase soil nutrient availability. Because Proteobacteria are generally regarded as copiotrophic bacteria that thrive in nutrient-rich environments [50], these conditions favor their enrichment, thereby potentially promoting soil nutrient cycling and crop productivity. We found that the relative abundance of Chloroflexi was higher in SL than in agricultural lands at low and medium elevations, whereas the opposite pattern was observed at high elevations. This difference may be attributed to the oligotrophic nature of phylum Chloroflexi, which generally thrive in nutrient-poor environments [51]. Consistent with this interpretation, Chloroflexi abundance was significantly negatively correlated with soil NO₃⁻-N concentrations across the elevation gradient, indicating that increased nitrogen availability may suppress their proliferation. Furthermore, the relative abundances of the three dominant bacterial phyla, namely, Acidobacteriota, Proteobacteria, and Chloroflex, exhibited distinct elevation patterns among different land-use types. These findings suggest that the effects of land use on soil bacterial community composition are elevation-dependent, highlighting the interactive influence of anthropogenic and environmental factors on microbial community assembly [26]. At the family level, both land-use types and elevation gradients significantly influenced bacterial community composition. At low elevation, the relative abundance of Pyrinomonadaceae was higher in shrubland soils than in agricultural soils. As a member of the Acidobacteriota, Pyrinomonadaceae possesses the capacity to degrade plant cell wall polysaccharides and plays an important role in litter decomposition [52]. The greater abundance of this family in SL soils may therefore be associated with the accumulation of plant-derived organic matter and litter inputs. At medium elevation, the abundance of Ktedonobacteraceae (phylum Chloroflexi) in shrubland soils was higher than in agricultural lands. Subgroup_2_family (phylum Acidobacteria) also exhibited a similar trend. These acidophilic, oligotrophic bacteria could be more competitive in SL soils, whereas the increased availability of nutrients from agricultural inputs might have reduced their competitive advantage and limited their abundance [53]. At high elevation, the relative abundances of Vicinamibacteraceae, Chitinophagaceae, and Gemmatimonadaceae in shrubland soils were lower than those in agricultural lands. This pattern suggests that agricultural management at high elevations alters soil environmental conditions in ways that favor the proliferation of these bacterial groups. Collectively, these findings suggest that the responses of dominant bacterial families to land-use change vary across elevations, reflecting the combined effects of environmental gradients and agricultural disturbance on soil bacterial communities.

Redundancy analysis (RDA) showed that the nine measured soil chemical properties explained 86.35%, 86.88%, and 83.75% of the total variation in soil bacterial community composition at low, medium, and high elevations, respectively, suggesting that soil chemical properties were major drivers of bacterial community variation across all elevation gradients (Fig. 5). At low and medium elevations, soil NO₃^--N was identified as a key environmental factor shaping bacterial community composition. This is likely because NO₃^།-N serves as a readily available nitrogen source for microorganisms [54], and changes in its concentrations directly affect soil nitrogen availability, thereby influencing the composition of soil bacterial communities. In addition, TP was an important factor affecting bacterial community composition at medium elevation, suggesting that soil phosphorus availability also plays a critical role in shaping bacterial community composition. At high elevation, NH₄⁺-N and TN were the key environmental factors associated with variations in soil bacterial community composition. Therefore, regardless of elevation, soil nitrogen appears to play a critical role in shaping the β diversity of the soil bacterial community in this region. In addition, soil pH, TC, SOC, and DOC were also significantly associated with variations in bacterial community composition, as these factors provide essential resources and environmental conditions for microbial growth and survival. For example, soil bacteria are highly sensitive to changes in soil pH, and even slight fluctuations can markedly alter bacterial community composition [55]. Furthermore, SOC is closely associated with soil bacterial communities as it serves as a major source of energy for microbial metabolism [56]. Overall, land use types exerted a stronger and more direct influence on soil bacterial community composition than elevation. Nevertheless, both factors significantly modified soil environmental conditions, and thereby shaped the composition and distribution patterns of soil bacterial communities.

Fig. 5.

Correlation between soil bacterial community composition and environmental factors. a-c RDA analysis of bacterial community with environmental factors; (d-f) correlation analysis between dominant phyla and environmental factors. SL: shrublands; CF: coffee fields; MF: maize fields; OF: orange fields. TC, total carbon; TN, total nitrogen; TP, total phosphorus; NH₄⁺-N, ammonium nitrogen; NO₃^--N, nitrate nitrogen; SOC, soil organic carbon; DOC, dissolved organic carbon; C:N, C:N ratios. * p<0.05, ** p<0.01, ***p<0.001

Effects of land use types, elevation, and their interactions on C and N cycling function of soil bacterial communities

C and N cycling are fundamental ecological processes, and represent key areas of research in terrestrial ecosystem functioning and soil biogeochemistry [57]. Two-way analysis of variance showed that land use types, elevation gradients, and their interactions significantly affected the abundance of functional genes associated with C and N cycling (Fig. 6). Regarding the effect of land use types, at both low and high elevations, the abundances of C and N cycling functional genes were significantly lower in CF, MF, and OF than in SL. This pattern may be attributed to agricultural management practices, which disrupt soil structure, reduce litter inputs, and alter resource availability [58]. Consequently, the abundance of functional microbial groups involved in soil C and N cycling is reduced, leading to shifts in the functional structure of soil bacterial communities as they adapt to the altered environmental conditions. Notably, at medium elevation, the abundance of functional genes associated with C and N cycling was significantly higher in OF than in SL. This finding suggests that organic orange cultivation at medium elevation might have created a more favorable microenvironment for C and N transformation, thereby promoting the growth and activity of microorganisms involved in these processes. The effects of elevation gradients on the abundance of functional genes were also dependent on land use types. In SL, the abundance of functional genes associated with C and N cycling initially decreased and then increased with increasing elevation, reaching its highest level at high elevations. This pattern may be attributed to the lower temperatures at high elevation, which slow down the decomposition of organic matter [59], and promote the accumulation of soil organic carbon and dissolved organic carbon in SL soils. The increased availability of these carbon resources may provide favorable conditions for the growth and activity of microorganisms involved in C and N cycling. Notably, SL and the three agricultural land-use types exhibited distinct elevation patterns in the abundance of C and N cycling functional genes, highlighting the substantial effects of intensive human disturbance on microbial functional responses to elevation. These patterns are likely driven by complex interactions among soil environmental factors, land use, and elevation [13, 60], which collectively regulate soil biogeochemical processes, including carbon, nitrogen, and sulfur cycling [61, 62]. At high elevation, the abundance of functional groups involved in C and N cycling was significantly negatively correlated with soil pH, whereas a significant positive correlation was observed at medium elevations, suggesting that soil pH is a key factor regulating microorganisms associated with C and N cycling [13]. In addition, soil total carbon, soil organic carbon, and dissolved organic carbon were all significantly positively correlated with the abundance of C and N cycling functional groups (Table 2), indicating that soil carbon resources play an important role in shaping the functional potential of soil bacterial communities [44]. Therefore, assessments of the effects of land use on soil bacterial functions should also consider the influence of elevation-related environmental conditions to achieve a more comprehensive understanding of microbial functional responses.

Table 2.

Correlation of C and N cycling functional groups with chemical properties

Elevation	Functional group	pH	TC (g/kg)	TN (g/kg)	TP (g/kg)	NO4+-N (mg/kg)	NO3--N (mg/kg)	SOC (g/kg)	DOC (g/kg)	C: N
Low elevation	C cycling	0.57	-0.03	-0.09	-0.12	-0.13	-0.79**	-0.03	0.11	0.43
	N cycling	0.60*	0.12	-0.04	-0.09	-0.13	-0.81**	0.02	0.17	0.47
Medium elevation	C cycling	0.69*	0.62*	0.44	0.04	0.24	0.14	0.59*	0.69*	-0.13
	N cycling	0.85**	0.73**	0.45	-0.16	-0.04	0.15	0.70**	0.82**	-0.04
High elevation	C cycling	-0.61*	0.85**	0.93**	0.76**	0.77**	0.73**	0.94**	0.90**	0.12
	N cycling	-0.77**	0.68*	0.94**	0.54	0.94**	0.86**	0.90**	0.77**	-0.16

TC Total carbon, TN Total nitrogen, TP Total phosphorus, NH₄⁺-N Ammonium nitrogen, NO₃^--N Nitrate nitrogen, SOC Soil organic carbon, DOC Dissolved organic carbon, C:N, C:N ratios. * p<0.05, ** p<0.01

Conclusions

In this study, we combined 16 S rRNA amplicon sequencing with FAPROTAX functional annotation to comprehensively assess the effects of land use types and elevation gradients on the composition, diversity, and functional potentials of soil bacterial communities in the Gaoligong Mountains, as well as the underlying environmental drivers. The results showed that land use types, elevation gradients, and their interactions significantly affected soil chemical properties, soil bacterial community α diversity (Observed, Shannon, and ACE indices), and the abundance of C and N cycling functional genes. In addition, the relative abundances of dominant bacterial phyla and families varied markedly across land use types and elevations, with these variations being strongly associated with soil nutrients and pH. Notably, although both land use types and elevation gradients significantly influenced β diversity of soil bacterial communities, the effect of land use types was stronger and more direct than that of elevation. Moreover, soil nitrogen was identified as a key environmental factor regulating soil bacterial community composition in this region. These findings suggest that land use exerts a stronger and more direct influence on soil bacterial community composition than elevation. Nevertheless, both factors modify soil environmental conditions and thereby shape the composition and distribution patterns of soil bacterial communities. Consequently, a comprehensive assessment of the impacts of human disturbance on soil bacterial functions should also consider the influence of elevation-related environmental conditions.

Abbreviations

SL

Shrublands

CL

Coffee fields

MF

Maize fields

OF

Orange fields

TC

Total carbon

TN

Total nitrogen

TP

Total phosphorus

NH₄⁺-N

Ammonium nitrogen

NO₃^--N

Nitrate nitrogen

SOC

Soil organic carbon

DOC

Dissolved organic carbon

C

N: C:N ratios

Authors' contributions

Ruilong Huang and Wei Li conceived the study and designed the research methodology; Ruilong Huang and Wei Li were responsible for data collection; Ruilong Huang was responsible for data analysis and visualization; Ruilong Huang and Wei Li were responsible for drafting and revising the manuscript; Ruilong Huang was responsible for revising the manuscript based on the reviewers’ comments. All authors contributed critically to the drafts and gave final approval for publication.

Funding

This research was funded by Yunnan Provincial Key Research and Development Program—Special Project for Social Development: “Community Sustainable Development Model and Demonstration Based on Nature-Based Solutions” (202303AC10001203).

Data availability

The datasets supporting the conclusions of this article are available in the National Center for Biotechnology Information (NCBI) under BioProject number PRJNA1467104.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.